This study

Deep learning has the potential to revolutionize process analytical technology in the pharmaceutical industry. Here, we used Raman spectroscopy-based deep learning strategies to develop a tool for detecting microbial contamination. We built a Raman dataset for microorganisms that are common contaminants in the pharmaceutical industry for Chinese Hamster Ovary (CHO) cells, which are often used in the production of biologics. Using a convolution neural network (CNN), we classified the different samples comprising individual microbes and microbes mixed with CHO cells with an accuracy of 95-100%. The set of 12 microbes spans across Gram-positive and Gram-negative bacteria as well as fungi. We also created an attention map for different microbes and CHO cells to highlight which segments of the Raman spectra contribute the most to help discriminate between different species. This dataset and algorithm provide a route for implementing Raman spectroscopy for detecting microbial contamination in the pharmaceutical industry.

The biological reduction of ferrous ethylenediaminetetraacetic acid (EDTA-FeII-NO and EDTA-FeIII) is an important process in integrated electrobiofilm reduction method, and this method has been regarded as a promising alternative for removing NOx from industrial boiler flue gas. EDTA-FeII-NO and EDTA-FeIII are crucial substrates that should be biologically reduced at a high rate. However, they would inhibit one another’s reduction processes when they are present together, which might limited the further promotion of this integrated method. In this study, an integrated electrobiofilm reduction system with high reduction rate of EDTA-FeII- NO and EDTA-FeIII was established. The microbial communities in electrobiofilms were mainly studied to analyze their changes during the reduction of these two substrates under different conditions. It presents a better performance of substrates- resistance shock loading and high microbial diversities compared with the conventional chemical absorption-biological reduction system. High-throughput sequencing analysis showed that the changes in concentrations of EDTA-FeII-NO and EDTA-FeIII significantly impacted the genera of the microbial community. Alicycliphilus, Enterobacteriaceae and Raoultella were found to be the dominant genera (>25%, respectively) involved in EDTA-FeII-NO reduction. As an EDTA-FeIII reducing bacteria, Chryseobacterium can endure shock loading of substrates. Ochrobactrum can reduce nitrate using electrons and exhibited better stability under shock loading. Furthermore, higher microbial diversity and stable reactor operation could be achieved when the concentrations of EDTA-FeII-NO and EDTA-FeIII approached the same value.

γ-Aminobutyric acid (GABA) is a non-protein amino acid produced from the decarboxylation of glutamate by glutamate decarboxylase. Corynebacterium glutamicum is the most promising host of γ-aminobutyric acid production for its inherent glutamate precursor supply. However, the intracellularly expressed glutamate decarboxylase in C. glutamicum showed the weak catalysis capacity on the conversion of glutamate to γ-aminobutyric acid. Here we designed an different catalysis scenario by secretively overexpressing the glutamate decarboxylase in C. glutamicum and moving the decarboxylation reaction into the extracellular space for GABA synthesis. A signal peptide in the expression cassette directed the successful secretion of glutamate decarboxylase in C. glutamicum. The extracellular catalysis by secreted glutamate decarboxylase increased the γ-aminobutyric acid generation by three-folds, comparing with that by intracellular catalysis. Further efforts on enhancing the expression of glutamate decarboxylase and decreasing the degradation of γ-aminobutyric acid improved γ-aminobutyric acid generation by 39%. The fed-batch fermentation of the engineered C. glutamicum strain reached the record high titer (77.6g /L), overall yield (0.37 g/g glucose), and productivity (1.21 g/L/h) of γ-aminobutyric acid production. This study demonstrated a unique design of extracellular catalysis for efficient γ-aminobutyric acid production by C. glutamicum.

Therapeutic monoclonal antibodies and related products have steadily grown to become the dominant product class within the biopharmaceutical market. Production of antibodies requires special precautions to ensure safety and efficacy of the product. In particular, minimizing antibody product heterogeneity is crucial as drug substance variants may impair the activity, efficacy, safety and pharmacokinetic properties of an antibody, consequently resulting in the failure of a product in pre-clinical and clinical development. This review will cover the manufacturing and formulation challenges and advances of therapeutic monoclonal antibodies, with a focus on improved processes to minimize variants and ensure batch-to-batch consistency. Processes put in place by regulatory agencies such as Quality-by-Design (QbD) and current Good Manufacturing Practices (cGMP) will be reviewed, and how their implementation has aided drug development in pharmaceutical companies. Advances in formulation and considerations on the intended use of a therapeutic antibody, including route of administration and patient compliance, will be discussed.

The oleaginous yeast Yarrowia lipolytica is an important industrial microorganism used for the production of lipids, proteins and various chemicals. The design of effective biotechnological processes with this cell factory requires an in-depth knowledge of its metabolism. Here we present a transcriptomic study of Y. lipolytica grown in the presence of two important carbon sources, namely glycerol and glucose, as well as in a mixture of both at different carbon to nitrogen ratios. It emerged that the transcriptomic landscape of Y. lipolytica is more sensitive to the nitrogen availability than to the utilized carbon source, as evidenced by more genes being differentially expressed in lower carbon to nitrogen ratio. In particular, expression of hexokinase (HXK1) is significantly susceptible to changes in nitrogen concentrations. Moreover, high HXK1 expression in low nitrogen seems to impact the expression of other genes which are implicated in tricarboxylic acid cycle and erythritol biosynthesis. We further show that expression of HXK1 and two genes belonging to the sugar porter family might be controlled by GATA-like zinc-finger proteins.

With the pandemic emergence of SARS-CoV-2, the exposure of cell substrates used for manufacturing of medicines has become a possibility. Cell lines used in biomanufacturing were thus evaluated for their SARS-CoV-2 susceptibility, and the detection of SARS-CoV-2 in culture supernatants was tested by routine adventitious virus testing of fermenter harvest.

Current technological developments in the field of wireless communications has enabled the use of ultra-low power, lightweight, miniature types of smart health monitoring devices which are integrated into a Wireless Body Sensor Network (WBSN). Vital signs in humans such as temperature, heartbeat, and pulse can be tracked and detected from a remote location with help of biomedical wireless sensors. This article proposes a method to securely encrypt the patient’s data and transmit it to the authorized doctor using wireless devices with in the hospital premises. This article is aimed at generating electrocardiogram (ECG) based key agreement scheme for the sake of generating a common key in a body area network. This kind of smart health information communication method by means of sensors and internet connection to servers is more confidential and encrypted to protect the patient’s health data. Security and Privacy mechanisms use a significant part of the available energy and should therefore be energy efficient and light weight. The Proposed work in this article is implemented in Telosb running ContikiOS. The TelosB mote is designed for experimentation with low-power personal wireless area network (LoWPAN) with IEEE 802.15.4/ZigBee/Telosb compliant RF transceiver. By using iris or fingerprints, the security of this technique can be further improved.

The goal of this research is to leverage computational molecular biophysics to guide process development, reduce experimental burden and focus purification activities on feasible targets. Here, we distill a complex separation problem (e.g. chromatographic retention of monoclonal antibodies) into a tangible model (ligand/protein complex), which is computationally feasible while preserving enough detail (atomistic level for interaction site) to support industrially relevant separation challenges. Computational docking, coupled with molecular dynamics simulation, produces results that are directionally consistent with chromatography for proteins (mAb). This approach is generalizable and can be applied to a range of ligands (AEX, CEX, and Mixed Mode). A detailed model of the chromatography base matrix (agarose) was constructed to obtain a biophysical understanding of potential protein/base matrix interactions. The base matrix was then modified in silico with ligands over a range of ligand densities representative of commercial chromatography resins to generate an agarose/ligand complex. A generic approach was developed to model the impact of avidity and ligand density on mAb/ligand interaction. The results revealed that increasing ligand density mask contributions of base matrix binding. Increasing the number of ligands that can interact with mAb results in more favorable free energy of binding or ΔG (more negative) with a limited incremental increase in ΔG by increasing N (number of ligands per agarose cluster) above three. Additionally, for protein/ligand interactions at each binding site, not all ligands contribute equally to the binding affinities or interaction energies and a redistribution of binding interactions/energies occur as N increases. These observations yield insights into the impact of avidity on retention (macroscopic affinity measurement via k’). The generic approach described in this manuscript can be leveraged to inform resin selection and design as well as targeted ligand selection/purification development in a rational manner.

Glutarate is an attractive C5 platform chemical having wide application in nylon and plasticizer. However, microbial glutarate is mainly accumulated in the degradation of lysine and other methods were rarely explored for producing the glutarate from glucose directly. Here, we utilized a reversed adipic acid degradation pathway (RADP) and improved the glutarate production by increasing the precursors (malonyl-CoA and acetyl-CoA) based on the previously studied strain Bgl4146. Specifically, the conversion system of intracellular acetyl-CoA to malonyl-CoA was firstly constructed and optimized to balance acetyl-CoA synthase and acetyl-CoA carboxylase under different dissolved oxygen, enhancing the glutarate production from 0.09 g/L to 0.49 g/L. Then, modulating CoA balance by monitoring the expression of acetate kinase and pyruvate dehydrogenase resulting in a rise in glutarate titer up to 0.70 g/L. Finally, the optimized strain Bgl51464 was able to produce 7.97 g/L glutarate in a 5-L bioreactor. This strategy was described here, which could lay a certain foundation for the development of effective CoA balance to produce industrially high value-added chemicals.

Bacillus subtilis is an attractive host for directed evolution of the enzymes whose substrates cannot be transported across the cell membrane. However, generation of mutant library in B. subtilis still suffers problems of small library size, plasmid instability and heterozygosity. Here, large library of random mutant was created through inserting error-prone PCR (epPCR) product to the chromosome of B. subtilis. Specifically, epPCR product was fused with flanking regions and antibiotic resistant marker using a PCR-based multimerization method, generating insertion construct. epPCR product was integrated into chromosome via homologous recombination after insertion construct was transformed into the supercompetent cells of B. subtilis strain SCK6. The transformation efficiency of insertion construct was improved though increasing the number of competent cell and the length of flanking regions. A library containing 3.5×105 random mutant was construction using per μg insertion construct, which is sufficient for directed evolution. Moreover, the library generation process could be accomplished within one day. The effectiveness of this method was confirmed by improving the activity of Methyl Parathion Hydrolase (MPH) toward chlorpyrifos and to enhance the secretion level of MPH in B. subtilis. Taken together, present work provides a fast and efficient method to integrate epPCR product into the chromosome of B. subtilis, facilitating directed evolution and expression optimization of target protein.

Avian transgenesis has served as a suitable approach to generate bioreactors for the manufacturing of recombinant proteins. Production in chicken cells comes with significant advantages over other systems including providing the human-like glycosylation on target proteins. In this regard, the oviduct-specific ovalbumin promoter has been one of the ideal candidates to drive the expression of transgenes. Previous plasmid-based studies on the regulatory sequences of ovalbumin promoter have led researchers to exploit ovalbumin regulatory elements out of their native genomic context (ex situ) to direct transgene expression in the transgenic chicken bioreactors. Although the inherent limitations on the ex situ use of ovalbumin promoter have promoted the use of native ovalbumin promoter for the expression of a transgene, generation of transgenic chicken is relatively difficult, inefficient, and time-consuming. To overcome these obstacles, in this study we show that CRISPR-mediated deletion of some distal ovalbumin promoter sequences in a non-oviduct cell can lead to the significant expression of the ovalbumin gene, and also a knocked-in reporter, in an estrogen-independent manner. These findings overcome the limitation of cloned promoters, where the promoter regulatory sequences have to be taken out of their cis context and also their native spatial nuclear organization into a plasmid.

The synthesis of starch-based physical hydrogels in combination with chitosan and polyvinyl alcohol, and their potential co-application with chitosan nanoparticles was evaluated. The potential of starch-chitosan hydrogel obtained by physical/chemical method for tissue engineering uses was also studied in a mouse wound healing model. Although the microscopical structure of each synthesized hydrogel suggests a possible biological application, starch-polyvinyl alcohol hydrogel exhibited rigid behavior with minor channel diameters, a lower swelling rate (less than 300%), and negatively affected cell viability in a cytotoxicity assay. Starch-chitosan hydrogel obtained by chemical crosslinking with glutaraldehyde demonstrated the higher swelling rate (about 1100%), cell viability values over 80%, and a homogeneous tri-dimensional structure; along with an excellent interaction with chitosan nanoparticles. This type of hydrogel was selected for an in vivo experiment, showing significant differences in wound healing process against a non-treated control, in terms of inflammation, exudate production and tissue recovering.

Stem cell (SC) differentiation towards somatic cells has proven to be an effective technique in the understanding and progression of regenerative medicine. Despite improvements, concerns regarding the efficiency of differentiation and the differences between SC products and their in vivo counterparts must be addressed. Biomaterials that mimic endogenous growth conditions represent one recent method used to improve the quality and efficiency of SC differentiation. Here, we aim to use bioinformatics approaches to accomplish two aims: 1) determine the effect of different biomaterials on SC growth and differentiation, and 2) understand the effect of cell of origin on the differentiation potential of multipotent SCs. First, we demonstrate that the dimensionality (2D versus 3D) and the degradability of biomaterials affects the way that the cells are able to grow and differentiate at the transcriptional level. Additionally, the particular cell of origin is an important factor in determining the response of SCs to same biomaterial transcriptionally. Our data demonstrates the ability of bioinformatics to understand novel molecular mechanisms and context by which SCs are most efficiently able to differentiate. These results and strategies may suggest proper combinations of biomaterials and SCs to achieve high differentiation efficiency and functionality of desired cell types.

The hemibiotrophic oomycetes are significant threats to a wide range of Cucurbitaceae species, causing substantial losses of plant productions. Particularly, Phytophthora melonis evokes severe symptoms, thus dramatically limiting yield in cucumber. However, information about cucumber–P. melonis interaction is still limited. This study explored changes in the activities of phenylalanine ammonia-lyase (PAL), peroxidase (POX), catalase (CAT), superoxide dismutase (SOD), and polyphenol oxidase (PPO) in cucumber roots of two resistant genotypes (Soheil and Ramezz), one moderately resistant genotype (Baby) and three highly susceptible genotypes (Extrem, Mini 6-23 and Yalda), over the time courses of 7, 14 and 21 days after inoculation (DAI). The results indicated that the activities of defence‐related enzymes differed between the resistant and highly susceptible genotypes. Although, the defense-related enzymatic activities were elevated sharply in the resistant and moderately resistant genotypes after inoculation, but no significant correlations were present between the activity trends of PPO, SOD and CAT and resistance characteristics. Moreover, no significant changes in enzyme activities were found in the control plants, non-inoculated plants of the six genotypes during the testing period. Altogether, the resistance of cucumber to P. melonis is related to POX and PAL activities, but does not show relationship with PPO, SOD and CAT activities. Studying the physiological metabolic pathways of POX and PAL appears to be an important direction in research to elucidate resistance to P. melonis in cucumber genotypes.

Based on the analysis of CpxP genes among Escherichia coli strains, CpxP gene-targeting short guide RNA (sgRNA) was designed and inserted into the pGL3-MGP-RNA. The donor sequences (MG-HR) for homologous repair were designed and cloned by PCR. MG-HR and pGL3-MGP-RNA were transformed into E. coli MG1655 (pCas9). The CpxP gene expression cassette was amplified by PCR and subcloned into pBBR1MCS-2. Then the pBBR-CpxP was independently transformed into E. coli MG1655. The results of motility experiment suggest that CpxP gene had a significant effect on the movement ability of E. coli strain. The CpxP protein had a significant inhibition of bacterial activity. The lastest 81 CpxP proteins sequences were selected and analyzed by multi-sequence alignment and molecular cluster. The CpxP proteins were roughly divided into three categories. Our results suggest that the CpxP protein was involved in bacterial motility, infection and pathogenicity.

Continuous improvements of cell-free synthesis (CFS) systems have generated interest in adopting the technology for the manufacture of biologics. This paper provides an evaluation of the manufacturing cost-effectiveness of CFS for a range of commercial scenarios. The evaluation was performed using an advanced techno-economic engine (TEE) built in Python. The TEE is programmed in an object-oriented environment capable of simulating a plethora of process flowsheets and predicting size and cost metrics for the process and the facility. A case study was formulated to compare the economics of whole bioprocesses based on either a CFS system or a mammalian cell system (CHO) for the manufacture of an antibody drug conjugate (ADC) at different commercial product demand levels (100 – 1000kg/year). The analysis demonstrated the potential of CFS for the commercial manufacture of biologics and identified key cost drivers related with the system. The CFS system showed approximately a two-fold increase in the cost of goods compared to CHO with a significant cost attributed to the in-house manufacture of the bacterial cell extract, necessary for the CFS reaction step in the process. A sensitivity and target analysis highlighted the impetus for further process improvements especially in the titre for the CFS process to become more competitive against well-established systems.

Background: Increasing the use of tobacco by the younger generation has increased in oral cavity tumours. Surgical treatment is radical and results in severe functional morbidity. Using computer-aided designing technology, surgical and rehabilitative planning can be better. We present here our concept of a biomechanical 3D tongue model and its clinical utility in the management of tongue tumours. Methods: Patients diagnosed with Carcinoma of Tongue were included. These patients underwent a pre-operative Magnetic Resonance Imaging (MRI) of the head and neck region at our center. These patients were informed about the use of a 3D biomechanical patient-specific model for treatment planning and execution. Using Materialise Mimics Innovation Suite 19 DICOM data was imported, visualized, edited and segmented. Flashforge ‘Creator-pro’3D Printer was used for 3D Printing. Fused Deposition Modeling (FDM) technology was used to print the tumour and uninvolved tongue in two different colors for easy identification. These patients underwent surgery with the 3D model serving as a guide for margins. Results: Two patients with stage III squamous cell carcinoma of tongue underwent the surgery based on the plan evolved from the 3D model. All the surgical margins were clear. The model helped address the discordance between patient expectations and surgical outcomes. We found that the model aided the reconstructive surgeon to plan the flap volume better and this translated into better rehabilitative outcomes. Discussion and Conclusion: The 3D biomechanical tongue model is a novel concept and may aid in improving our overall treatment outcomes.