This paper presents the development and testing of a low-cost (< $60), portable, electrical impedance based microflow cytometer for single cell analysis under controlled oxygen microenvironment. The system is based on an AD5933 impedance analyzer chip, a microfluidic chip, and an Arduino microcontroller operated by a custom Android application. A representative case study on human red blood cells (RBCs) affected by sickle cell disease is conducted to demonstrate the capability of the cytometry system. An equivalent circuit model of a suspended biological cell is used to interpret the electrical impedance of single flowing RBCs. RBCs exhibit decreased mean membrane capacitance by 24% upon hypoxia treatment while the mean cytoplasmic resistance remains consistent. RBCs affected by sickle cell disease exhibit decreased cytoplasmic resistance and increased membrane capacitance upon hypoxia treatment. Strong correlations are identified between the changes in the cells’ subcellular electrical components and the hypoxia-induced cell sickling process. The results reported in this paper suggest that the developed method of testing demonstrates the potential application for low-cost screening technique for sickle cell disease and other diseases in the field and low-resource settings. The developed system and methodology can be extended to analyze cellular response to hypoxia in other cell types.

The challenge of introducing new technologies into established industries is not a problem unique to the biopharmaceutical industry. However, it may be critical to the long-term competitiveness of individual manufacturers and, more importantly, the ability to deliver therapies to patients. This is especially true for new treatment modalities including cell and gene therapies. We review several barriers to technology adoption which have been identified in various public forums including business, regulatory, technology, and people-driven concerns. We also summarize suitable enablers addressing one or more of these barriers along with some suggestions for developing additional synergies.

Herein we report the use of Pseudomonas putida F1 biofilms grown on carbonized cellulosic fibers to achieve biodegradation of airborne VOCs in the absence of any bulk aqueous phase media. It is believed that direct exposure of gaseous VOC substrates to biomass may eliminate aqueous phase mass transfer resistance and facilitate VOC capture and degradation. When tested with toluene vapor as a model VOC, the supported biofilm could grow optimally at 300 ppm toluene and 80% relative humidity, with a specific growth rate of 0.425 day -1. During long-term VOC biodegradation tests in a tubular packed bed reactor, biofilms achieved a toluene degradation rate of 2.5 mg g DCW -1 h -1 during the initial exponential growth phase. Interestingly, the P. putida F1 film kept biodegrading activity even at the subsequent stationary non-growth phase. The supported biofilms with a biomass loading of 20% (wt) could degrade toluene at a rate of 1.9 mg g DCW -1 h -1 during the stationary phase, releasing CO 2 at a rate of 6.4 mg g DCW -1 h -1 at the same time (indicating 100% conversion of substrate carbon to CO 2). All the specific degradation rates are much higher than what can be gleaned from previously reported work. It also demonstrates the feasibility of biofilm growth and direct gas phase degradation of VOCs without requiring any bulk aqueous phase.

Biofilms can increase pathogenic contamination of drinking water, cause biofilm-related diseases, alter the sediment erosion rate, and degrade contaminants in wastewater. Compared with mature biofilms, biofilms in the early-stage have been shown to be more susceptible to antimicrobials and easier to remove. Mechanistic understanding of physical factors controlling early-stage biofilm growth is critical to predict and control biofilm development, yet such understanding is currently incomplete. Here, we reveal the impacts of hydrodynamic conditions and microscale surface roughness on the development of early-stage Pseudomonas putida biofilm through a combination of microfluidic experiments, numerical simulations, and fluid mechanics theories. We demonstrate that early-stage biofilm growth is suppressed under high flow conditions and that the critical local velocity for early-stage P. putida biofilms to develop is about 50 μm/s, similar to P. putida’s swimming speed. We further illustrate that microscale surface roughness promotes the growth of early-stage biofilms by increasing the area of the low-flow region. Furthermore, we show that the critical average shear stress, above which early-stage biofilms cease to form, is 0.9 Pa for rough surfaces, three times as large as the value for flat or smooth surfaces (0.3 Pa). The important control of flow conditions and microscale surface roughness on early-stage biofilm development, characterized in this study, will facilitate future predictions and managements of early-stage P. putida biofilm development on the surfaces of drinking water pipelines, blood vessels, and sediments in aquatic environments.

We report an automated cell-isolation system based on fluorescence image analysis of cell aggregates cultured in a photodegradable hydrogel. The system incorporates cell culture in a humidified atmosphere with controlled CO 2 concentration and temperature, image acquisition and analysis, micropatterned light exposure, and cell collection by pipetting. Cell aggregates were cultured on hydrogels, and target cells were selected by phase contrast and fluorescence image analysis. After degradation of the hydrogel by exposure to micropatterned ultraviolet light, cell aggregates were transferred to a collection vessel by robotic pipetting. We assessed the system for hydrogel degradation, recovery of target cells, and contamination by off-target cells. We demonstrated two practical applications of our method: (i) in cell aggregates from MCF-7-RFP strains in which 18.8% of cells produced red fluorescent protein (RFP), we successfully obtained 14 proliferative fluorescence-positive cell aggregates from 31 wells, and all of the isolated strains produced a higher proportion of RFP than the original populations; (ii) after fluorescent immunostaining of human epidermal growth factor receptor 2 (HER2) in cancer cells, we successfully isolated HER2-positive cells from a mixed population of HER2-positive and -negative cells, and gene sequence analysis confirmed that the isolated cells mainly contained the target cells.

With the further improvement of food safety requirements, the development of fast, high sensitivity, and portability methods for the determination of foodborne hazardous substances has become a new trend in the food industry. In recent years, biosensors and platforms based on functional nucleic acids and a range of signal amplification devices and methods have been established to allow rapid and sensitive determination of specific substances in samples by different methods, opening up a new avenue of analysis and detection. In this paper, functional nucleic acid types including aptamers, deoxyribozymes and G-quadruplexes which are commonly used in the detection of food source pollutants are mainly introduced, as well as nano signal amplification elements including quantum dots, noble metal nanoparticles, magnetic nanoparticles, DNA walkers, DNA logic gates. signal amplification technologies including nucleic acid isothermal amplification, HCR, CHA, biological barcode, and microfluidic system are combined with functional nucleic acid sensors and applied to the detection of many foodborne hazardous substances, such as foodborne pathogens, mycotoxins, residual antibiotics, residual pesticides, industrial pollutants, heavy metals, and allergens.Finally, the potential opportunities and broad prospects of functional nucleic acid biosensors in the field of food analysis are discussed.

The rapidly expanding market for regenerative medicines and cell therapies highlights the need to advance the understanding of cellular metabolisms and improve the prediction of cultivation production process for human induced pluripotent stem cells (iPSCs). In this paper, a metabolic kinetic model was developed to characterize underlying mechanisms of iPSC culture process, which can predict cell response to environmental perturbation and support process control. This model focuses on the central carbon metabolic network, including glycolysis, pentose phosphate pathway (PPP), tricarboxylic acid (TCA) cycle, and amino acid metabolism, which plays a crucial role to support iPSC proliferation. Heterogeneous measures of extracellular metabolites and multiple isotopic tracers collected under multiple conditions were used to learn metabolic regulatory mechanisms. Systematic cross-validation confirmed the model’s performance in terms of providing reliable predictions on cellular metabolism and culture process dynamics under various culture conditions. Thus, the developed mechanistic kinetic model can support process control strategies to strategically select optimal cell culture conditions at different times, ensure cell product functionality, and facilitate large-scale manufacturing of regenerative medicines and cell therapies.

Robotic facilities that can perform advanced cultivation (e.g., fed-batch or continuous) in high throughput have drastically increased the speed and reliability of the bioproduct development pipeline in the last decades. Still, developing reliable analytical technologies, that can cope with the throughput of the cultivation system, has proven to be very challenging. On the one hand, the analytical accuracy suffers from the low sampling volumes, and on the other hand, the number of samples that must be treated rapidly is very large. These issues have been a major limitation to implement feedback control methods in miniaturized bioreactor systems, where the observations of the process states are typically obtained after the experiment has finished. In this work, we implement a Sigma-Point Kalman filter in a high-throughput platform with 24 parallel experiments at the mL-scale to demonstrate its viability and added value in high throughput experiments. This method exploits the information generated by the ammonia-based pH control to enable the continuous estimation of biomass, a critical state to monitor the specific rates of production and consumption in the process. The objective in our case study is to ensure that the selected specific growth rate is tightly controlled throughout the complete Escherichia coli cultivations for recombinant production of antibody fragment.

Microfiltration is an essential step during biopharmaceutical manufacturing. However, unexpected flux decay can occur. Although the flux decay profile and initial flux are important factors determining microfiltration filterability, predicting them accurately is challenging since the root cause of unexpected flux decay remains elusive. In this study, the methodology for developing a prediction model of flux decay profiles was established. First, the filtration profiles of different monodisperse polystyrene latex and silica beads of various sizes were evaluated. These results revealed that the size and surface electrostatic properties of the beads affect the flux decay profile. Taking the size and surface electrostatic properties of protein aggregates into account, we constructed a predictive model using model bead filtration profiles. We showed that this methodology was applicable to two different microfiltration filters to predict the flux decay profile of therapeutic proteins. Since this prediction model is based on normalized flux, the initial flux must be predicted. We therefore successfully developed a method to predict initial flux based on the Hagen-Poiseuille equation using sample viscosity values for both filters. These prediction models can be used for effective microfiltration scale-up assessment and can be applied during early stage of process development.