An online monitoring device for measuring the concentration of four types of in-situ microorganisms by using the near-infrared band

Using optical density at 600 nm (OD600) to measure the microbial concentration is a popular approach due to its advantages like quick response and non-destructive. However, the OD600 measurement might be affected by the metabolic pigment, and it would become invalid when the solution dilution is insufficient. To overcome these issues, we proposed to adopt a more robust wavelength at 890 nm to quantify the attenuation of transmission light. After selecting this light source, we designed the light path and the circuit of the online monitoring device. Meanwhile, the random forest algorithm was introduced for temperature compensation and improving the stability of the device. This device was verified by monitoring the microbial concentration of four strains (Yeast, Bacillus, Arthrobacter, and Escherichia coli). The experimental result suggested that the mean absolute percentage error reached 4.11 %, 4.28 %, 4.49 %, and 4.53 % respectively, which is helpful to improve the accuracy of microbial concentration measurement.

An Online Support Vector Machine Algorithm for Dynamic Social Network Monitoring

Online monitoring of social networks offers exciting features for platforms, enabling both technical and behavioral analysis. Numerous studies have explored the adaptation of traditional quality control methods for detecting change points within social networks. However, the current research studies face limitations such as an overreliance on case-based attributes, high computational costs, poor scalability with large networks, and low sensitivity in fast change point detection. This paper proposes a novel algorithm for social network monitoring using One-Class Support Vector Machines (OC-SVMs) to address these limitations. Additionally, using both nodal and network-level attributes makes it versatile for diverse social network applications and effectively detecting network disturbances. The algorithm utilizes a well-defined training data dictionary with an updating procedure for evolutionary networks, enhancing memory and time efficiency by reducing the processing of input data. Extensive numerical experiments are conducted using an EpiCNet model to simulate interactions in an online social network, covering six change scenarios to evaluate the proposed methodology. The results show lower Average Run Length (ARL) and Expected Delay Detection (EDD), demonstrating the superior accuracy and effectiveness of the OC-SVM algorithm compared to alternative methods. Applying OC-SVM to the Enron Email network indicates its capability to identify change points, reflecting the tumultuous timeline that led to Enron's downfall. This further validates the substantial advancement of OC-SVM in social network monitoring and opens doors to broader real-world applications.

Real-time detection of mean and variance changes in experience sampling data: A comparison of existing and novel statistical process control approaches

Retrospective analyses of experience sampling (ESM) data have shown that changes in mean and variance levels may serve as early warning signs of an imminent depression. Detecting such early warning signs prospectively would pave the way for timely intervention and prevention. The exponentially weighted moving average (EWMA) procedure seems a promising method to scan ESM data for the presence of mean changes in real-time. Based on simulation and empirical studies, computing and monitoring day averages using EWMA works particularly well. We therefore expand this idea to the detection of variance changes and propose to use EWMA to prospectively scan for mean changes in day variability statistics (i.e.,s 2 , s , ln( s )). When both mean and variance changes are of interest, the multivariate extension of EWMA (MEWMA) can be applied to both the day averages and a day statistic of variability. We evaluate these novel approaches to detecting variance changes by comparing them to EWMA-type procedures that have been specifically developed to detect a combination of mean and variance changes in the raw data: EWMA-S 2 , EWMA-ln(S 2 ), and EWMA- X ¯ -S 2 . We ran a simulation study to examine the performance of the two approaches in detecting mean, variance, or both types of changes. The results indicate that monitoring day statistics using (M)EWMA works well and outperforms EWMA-S 2 and EWMA-ln(S 2 ); the performance difference with EWMA- X ¯ -S 2 is smaller but notable. Based on the results, we provide recommendations on which statistic of variability to monitor based on the type of change (i.e., variance increase or decrease) one expects.

Rapid online analysis of n-alkanes in gaseous streams via APCI mass spectrometry

Online monitoring of dynamic chemical processes involving a wide volatility range of hydrocarbon species is challenging due to long chromatographic measurement times. Mass spectrometry (MS) overcomes chromatographic delays. However, the analysis of n-alkane mixtures by MS is difficult because many fragment ions are formed, which leads to overlapping signals of the homologous series. Atmospheric pressure chemical ionization (APCI) is suitable for the analysis of saturated hydrocarbons and is the subject of current research. Still, although APCI is a "soft ionization" technique, fragmentation is typically inevitable. Moreover, it is usually applied for liquid samples, while an application for online gas-phase monitoring is widely unexplored. Here, we present an automated APCI-MS method for an online gas-phase analysis of volatile and semi-volatile n-alkanes. Mass spectra for n-heptane and n-decane reveal [M-H]+, [M-3H]+ and [M-3H+H2O]+ as abundant ions. While [M-H]+ and [M-3H]+ show an excessive fragmentation pattern to smaller CnH2n+1+ and CnH2n-1+ cations, [M-3H+H2O]+ is the only relevant signal within the CnH2n+1O+ ion group, i.e., no chain cleavage is observed. This makes [M-3H+H2O]+ an analyte-specific ion that is suitable for the quantification of n-alkane mixtures. A calibration confirms the linearity of C7 and C10 signals up to concentrations of ~1000-1500 ppm. Moreover, validated concentration profiles are measured for a binary C7/C10 mixture and a five-alkane C7/C10/C12/C14/C20 mixture. Compared to the 40-min sampling interval of the reference gas chromatograph, MS sampling is performed within 5 min and allows dynamic changes to be monitored.

A "Prediction - Detection - Judgment" framework for sudden water contamination event detection with online monitoring

The contamination detection technology helps in water quality management and protection in surface water. It is important to detect sudden contamination events timely from dynamic variations due to various interference factors in online water quality monitoring data. In this study, a framework named "Prediction - Detection - Judgment" is proposed with a method framework of "Time series increment - Hierarchical clustering - Bayes' theorem model". Time to detection is used as an evaluation index of contamination detection methods, along with the probability of detection and false alarm rate. The proposed method is tested with available public data and further applied in a monitoring site of a river. Results showed that the method could detect the contamination events with a 100% probability of detection, a 17% false alarm rate and a time to detection close to 4 monitoring intervals. The proposed index time to detection evaluates the timeliness of the method, and timely detection ensures that contamination events can be responded to and dealt with in time. The site application also demonstrates the feasibility and practicability of the framework proposed in this study and its potential for extensive implementation.

Raman spectroscopy applied to online monitoring of a bioreactor: Tackling the limit of detection

An in-situ monitoring model of alcoholic fermentation based on Raman spectroscopy was developed in this study. The optimized acquisition parameters were an 80 s exposure time with three accumulations. Standard solutions were prepared and used to populate a learning database. Two groups of mixed solutions were prepared for a validation database to simulate fermentation at different conditions. First, all spectra of the standards were evaluated by principal component analysis (PCA) to identify the spectral features of the target substances and observe their distribution and outliers. Second, three multivariate calibration models for prediction were developed using the partial least squares (PLS) method, either on the whole learning database or subsets. The limit of detection (LOD) of each model was estimated by using the root mean square error of cross validation (RMSECV), and the prediction ability was further tested with both validation datasets. As a result, improved LODs were obtained: 0.42 and 1.55 g·L-1 for ethanol and glucose using a sub-learning dataset with a concentration range of 0.5 to 10 g·L-1. An interesting prediction result was obtained from a cross-mixed validation set, which had a root mean square error of prediction (RMSEP) for ethanol and glucose of only 3.21 and 1.69, even with large differences in mixture concentrations. This result not only indicates that a model based on standard solutions can predict the concentration of a mixed solution in a complex matrix but also offers good prospects for applying the model in real bioreactors.

Highly sensitive resistance spectroscopy technique for online monitoring of biofilm growth on metallic surfaces

Online techniques for monitoring biofilm formation and evolution are limited, especially as regards its application in flowing water systems. This is chiefly due to the absence of efficient non-destructive and non-invasive sensing methods. In this study, a sensitive electrical resistance spectroscopy technique is developed to monitor non-invasively and in real time the growth of biofilms over metallic surfaces inside water flow systems. To this aim, Pseudomonas fluorescens strain is used for biofilm development lasting 72 h in a laboratory-scale test channel of orthogonal cross section. Biofilm development corresponds to a progressively increasing coverage of the metallic surface area up to full coverage and a progressively increasing thickness. Biofilm development is registered by continuous recording of electrical impedance signals (time series). Proper configuration and tuning of the electronics promote the resistive contribution to the signal whereas careful grounding diminishes electrical interferences and yields superb sensing sensitivity. An increase of relative electrical resistance of around 15% is noticed in 72 h flow experiments which is attributed to both an increase of metallic surface area coverage and an increase of biofilm thickness. An independent estimation of these quantities using imaging tools and microscopy analysis, indicates that full coverage of the metallic surface occurs after only 48 h of the flow experiment, whereas biofilm thickness increases gradually along the entire 72 h of the experiment. Cross-examination of electrical signals with biofilm characteristics (metallic surface coverage and biofilm thickness) reveals that, qualitatively speaking, electrical signals are rather more sensitive to metallic surface coverage than biofilm thickness.

Real-time online monitoring technology for sweeping frequency ultrasound (SFU) assisted extraction of amur grape (Vitis amurensis) seed oil

Sweeping frequency ultrasound (SFU) was used to assist extraction of amur grape (Vitis amurensis) seed (AGS) oil. Extraction conditions and physicochemical properties were optimized and analyzed under different extraction methods. Meanwhile, frequency and time domains were online monitored during SFU assisted extraction of AGS oil. PVDF piezoelectric sensor was used in time domain, and the hydrophone in frequency domain, so as to obtain the time-voltage waveform, signal power, spectrum distribution and other visual models. Physical models of the spatial peak acoustic intensity, charge quantity and work done by electric field force under different ultrasonic conditions were derived. The mathematical model between the work done by electric field force and the spatial peak acoustic intensity under the working state of PVDF piezoelectric sensor was constructed. Results show that the content of AGS oil by SFU assisted extraction was higher than that by organic extraction. Furthermore, the optimal single-frequency was 40 kHz and dual-frequency was 28/33 kHz, and SFU extraction time of 30 min was suitable with higher oil yield of 16.70 % and 16.94 %, respectively. In addition, the selection and combination of SFU also affected the oil oxidation degree. The peak voltage, spatial peak acoustic intensity, signal power and work of electric field force at 28/33 kHz were all higher than those at 40 kHz.

Towards a sustainable edge computing framework for condition monitoring in decentralized photovoltaic systems

In recent times, the rapid advancements in technology have led to a digital revolution in urban areas, and new computing frameworks are emerging to address the current issues in monitoring and fault detection, particularly in the context of the growing renewable decentralized energy systems. This research proposes a novel framework for monitoring the condition of decentralized photovoltaic systems within a smart city infrastructure. The approach uses edge computing to overcome the challenges associated with costly processing through remote cloud servers. By processing data at the edge of the network, this concept allows for significant gains in speed and bandwidth consumption, making it suitable for a sustainable city environment. In the proposed edge-learning scheme, several machine learning models are compared to find the best suitable model achieving both high accuracy and low latency in detecting photovoltaic faults. Four light and rapid machine learning models, namely, CBLOF, LOF, KNN, ANN, are selected as best performers and trained locally in decentralized edge nodes. The overall approach is deployed in a smart solar campus with multiple distributed PV units located in the R&D platform Green & Smart Building Park. Several experiments were conducted on different anomaly scenarios, and the models were evaluated based on their supervision method, f1-score, inference time, RAM usage, and model size. The paper also investigates the impact of the type of supervision and the class of the model on the anomaly detection performance. The findings indicated that the supervised artificial neural network (ANN) had superior performance compared to other models, obtaining an f1-score of 80 % even in the most unfavorable conditions. The findings also showed that KNN was the most suitable unsupervised model for the investigated experiments achieving good f1-scores (100 %, 95 % and 92 %) in 3 out of 4 scenarios making it a good candidate for similar anomaly detection tasks.

Automatically showing microbial growth kinetics with a high-performance microbial growth analyzer

It is difficult to show microbial growth kinetics online when they grow in complex matrices. We presented a novel strategy to address this challenge by developing a high-performance microbial growth analyzer (HPMGA), which employed a unique 32-channel capacitively coupled contactless conductivity detector as a sensing element and fixed with a CellStatz software. It was capable of online showing accurate and repeatable growth curves of well-dispersed and bad-dispersed microbes, whether they grew in homogeneous simple culture broth or heterogeneous complex matrices. Moreover, it could automatically report key growth kinetics parameters. In comparison to optical density (OD), plate counting and broth microdilution (BMD) methods, we demonstrated its practicability in five scenarios: 1) the illustration of the growth, growth rate, and acceleration curves of Escherichia coli (E. coli); 2) the antimicrobial susceptibility testing (AST) of Oxacillin against Staphylococcus aureus (S. aureus); 3) the determination of Ag nanoparticle toxicity on Providencia rettgeri (P. rettgeri); 4) the characterization of milk fermentation; and 5) the enumeration of viable pathogenic Vibrio in shrimp body. Results highlighted that the HPMGA method had the advantages of universality and effectivity. This technology would significantly facilitate the routine analysis of microbial growth in many fields (biology, medicine, clinic, life, food, environment, and ecology), paving an avenue for microbiologists to achieve research goals that have been inhibited for years due to a lack of practical analytical methods.

Development of a chemically defined medium for Paenibacillus polymyxa by parallel online monitoring of the respiration activity in microtiter plates

BACKGROUND

One critical parameter in microbial cultivations is the composition of the cultivation medium. Nowadays, the application of chemically defined media increases, due to a more defined and reproducible fermentation performance than in complex media. In order, to improve cost-effectiveness of fermentation processes using chemically defined media, the media should not contain nutrients in large excess. Additionally, to obtain high product yields, the nutrient concentrations should not be limiting. Therefore, efficient medium optimization techniques are required which adapt medium compositions to the specific nutrient requirements of microorganisms.

RESULTS

Since most Paenibacillus cultivation protocols so far described in literature are based on complex ingredients, in this study, a chemically defined medium for an industrially relevant Paenibacillus polymyxa strain was developed. A recently reported method, which combines a systematic experimental procedure in combination with online monitoring of the respiration activity, was applied and extended to identify growth limitations for Paenibacillus polymyxa. All cultivations were performed in microtiter plates. By systematically increasing the concentrations of different nutrient groups, nicotinic acid was identified as a growth-limiting component. Additionally, an insufficient buffer capacity was observed. After optimizing the growth in the chemically defined medium, the medium components were systematically reduced to contain only nutrients relevant for growth. Vitamins were reduced to nicotinic acid and biotin, and amino acids to methionine, histidine, proline, arginine, and glutamate. Nucleobases/-sides could be completely left out of the medium. Finally, the cultivation in the reduced medium was reproduced in a laboratory fermenter.

CONCLUSION

In this study, a reliable and time-efficient high-throughput methodology was extended to investigate limitations in chemically defined media. The interpretation of online measured respiration activities agreed well with the growth performance of samples measured in parallel via offline analyses. Furthermore, the cultivation in microtiter plates was validated in a laboratory fermenter. The results underline the benefits of online monitoring of the respiration activity already in the early stages of process development, to avoid limitations of medium components, oxygen limitation and pH inhibition during the scale-up.

Development of a simple biogas analyzer module (BAM) for real-time biogas production monitoring

AbstractAnaerobic digestion (AD) relies on the cooperation of specific microbial communities, making it susceptible to process disruptions that could impact biogas production. In this regard, this study presents a technological solution based on the Arduino platform, in the form of a simple online monitoring system that can track the produced biogas profile, named as biogas analyzer module (BAM). The applicability of the BAM focused on monitoring the biogas produced from sugarcane vinasse inoculated with sewage sludge biodigestion processed in mesophilic conditions (38 ^oC), in a pH range of 6.5-7.5, and following a three-stage operational model: (i) an adaptation (168 h), (ii) complete mixing (168 h), and (iii) bio-stimulation with glycerol (192 h). Then, the lab-made BAM was used to trace the produced biogas profile, which registered a total biogas volume of 8,719.86 cm³ and biomethane concentration of 95.79% (vol.), removing 90.8% (vol) of carbon dioxide (CO₂) and 65.2% (vol) of hydrogen sulfide (H₂S). In conclusion, the results ensured good accuracy and efficiency to the device created by comparisons with established standards (chromatographic and colorimetric methods), as well as the cost reduction. The developed device would likely be six times cheaper than what is available in the market.

A two-staged adsorption/thermal desorption GC/MS online system for monitoring volatile organic compounds

Real-time online monitoring of volatile organic compounds (VOCs) in ambient air is crucial for timely and effective human health protection. Here, we developed an innovative, automated two-staged adsorption/thermal desorption gas chromatography/mass spectrometry (GC/MS) system for real-time online monitoring of 117 regulated volatile organic compounds (VOCs). This system comprised a sampling unit, water management trap, two-staged adsorption/thermal desorption unit, thermoelectric coolers (TECs), and a commercial GC/MS system. By implementing a micro-purge-and-trap (MP & T) step and a two-staged adsorption/thermal desorption unit, the presence of interfering substances was effectively minimized. The utilization of a heart-cutting GC, combined with a single MS detector, facilitated the precise separation and detection of 117 C₂-C₁₂ VOCs, while circumventing the identification and coelution challenges commonly associated with traditional GC-FID or GC-FID/MS methods. The performance of our newly developed online system was meticulously optimized and evaluated using standard gas mixtures. Under optimal conditions, we achieved impressive results, with R² values ≥ 0.9946 for the standard linear curves of all 117 VOCs, demonstrating a precision (RSD) ranging from 0.2% to 6.4%. When applied in the field monitoring, the concentration drifts for 10 ppbv standard gas mixtures were 0.01-5.64% within 24 h. Our study developed a system for online monitoring of 117 atmospheric VOCs with relatively high accuracy and robustness.

[Design for online monitoring of occupational hazard factors based on internet of things]

At present, there are disadvantages with the detection for occupational hazard factors, such as insufficient monitoring data, poor timeliness, weak representativeness, long detection cycles, and inability to continuously monitor. Taking advantages of internet of things technology, an online monitoring platform for occupational hazard factors has been designed. The platform collects the concentration (intensity) of hazard factors through sensors, transmits the occupational hazards data collected online in realtime. The online monitoring cloud center for occupational hazard factors processes and analyzes online monitoring data in realtime, stores the hazard factors data to form database management, and provides user application services to form an intelligent online monitoring service model for occupational hazard factors. Based on the online monitoring platform of occupational hazard factors, multi-level government health supervision departments and employers can grasp the status of hazard factors in real time, which is conducive to improving the level of occupational hazard supervision.

Predicting microbial water quality in on-site water reuse systems with online sensors

Widespread implementation of on-site water reuse is hindered by the limited availability of monitoring approaches that ensure microbial quality during operation. In this study, we developed a methodology for monitoring microbial water quality in on-site water reuse systems using inexpensive and commercially available online sensors. An extensive dataset containing sensor and microbial water quality data for six of the most critical types of disruptions in membrane bioreactors with chlorination was collected. We then tested the ability of three typological machine learning algorithms - logistic regression, support-vector machine, and random forest - to predict the microbial water quality as "safe" or "unsafe" for reuse. The main criteria for model optimization was to ensure a low false positive rate (FPR) - the percentage of safe predictions when the actual condition is unsafe - which is essential to protect users health. This resulted in enforcing a fixed FPR ≤ 2%. Maximizing the true positive rate (TPR) - the percentage of safe predictions when the actual condition is safe - was given second priority. Our results show that logistic-regression-based models using only two out of the six sensors (free chlorine and oxidation-reduction potential) achieved the highest TPR. Including sensor slopes as engineered features allowed to reach similar TPRs using only one sensor instead of two. Analysis of the occurrence of false predictions showed that these were mostly early alarms, a characteristic that could be regarded as an asset in alarm management. In conclusion, the simplest algorithm in combination with only one or two sensors performed best at predicting the microbial water quality. This result provides useful insights for water quality modeling or for applications where small datasets are a common challenge and a general advantage might be gained by using simpler models that reduce the risk of overfitting, allow better interpretability, and require less computational power.

Yeast extracts from different manufacturers and supplementation of amino acids and micro elements reveal a remarkable impact on alginate production by A. vinelandii ATCC9046

BACKGROUND

In research and production, reproducibility is a key factor, to meet high quality and safety standards and maintain productivity. For microbial fermentations, complex substrates and media components are often used. The complex media components can vary in composition, depending on the lot and manufacturing process. These variations can have an immense impact on the results of biological cultivations. The aim of this work was to investigate and characterize the influence of the complex media component yeast extract on cultivations of Azotobacter vinelandii under microaerobic conditions. Under these conditions, the organism produces the biopolymer alginate. The focus of the investigation was on the respiration activity, cell growth and alginate production.

RESULTS

Yeast extracts from 6 different manufacturers and 2 different lots from one manufacturer were evaluated. Significant differences on respiratory activity, growth and production were observed. Concentration variations of three different yeast extracts showed that the performance of poorly performing yeast extracts can be improved by simply increasing their concentration. On the other hand, the results with well-performing yeast extracts seem to reach a saturation, when their concentration is increased. Cultivations with poorly performing yeast extract were supplemented with grouped amino acids, single amino acids and micro elements. Beneficial results were obtained with the supplementation of copper sulphate, cysteine or a combination of both. Furthermore, a correlation between the accumulated oxygen transfer and the final viscosity (as a key performance indicator), was established.

CONCLUSION

The choice of yeast extract is crucial for A. vinelandii cultivations, to maintain reproducibility and comparability between cultivations. The proper use of specific yeast extracts allows the cultivation results to be specifically optimised. In addition, supplements can be applied to modify and improve the properties of the alginate. The results only scratch the surface of the underlying mechanisms, as they are not providing explanations on a molecular level. However, the findings show the potential of optimising media containing yeast extract for alginate production with A. vinelandii, as well as the potential of targeted supplementation of the media.

Monitoring parameter change for bivariate time series models of counts

In this study, we consider an online monitoring procedure to detect a parameter change for bivariate time series of counts, following bivariate integer-valued generalized autoregressive heteroscedastic (BIGARCH) and autoregressive (BINAR) models. To handle this problem, we employ the cumulative sum (CUSUM) process constructed from the (standardized) residuals obtained from those models. To attain control limits, we develop limit theorems for the proposed monitoring process. A simulation study and real data analysis are conducted to affirm the validity of the proposed method.

Indoor air pollution from the household combustion of coal: Tempo-spatial distribution of gaseous pollutants and semi-quantification of source contribution

Coal is a widely used solid fuel for cooking and heating activities in rural households, whose incomplete combustion in inefficient household stoves releases a range of gaseous pollutants. To evaluate the impact of coal combustion on indoor air quality, this study comprehensively investigated the indoor air pollution of typical gaseous pollutants, including formaldehyde (HCHO), carbon dioxide (CO₂), carbon monoxide (CO), total volatile organic compounds (TVOC), and methane (CH₄), during coal combustion process in rural households using online monitoring with high tempo-spatial resolution. The indoor concentrations of gaseous pollutants were considerably elevated during the coal combustion period, with the indoor concentrations being significantly higher than those in courtyard air. The levels of several gaseous pollutants (CO₂, CO, TVOC, and CH₄) in indoor air were much higher during the flaming phase than the de-volatilization and smoldering phases, while HCHO peaked in the de-volatilization phase. The gaseous pollutant concentrations mostly decreased from the room ceiling to the ground level, while their horizontal distribution was relatively uniform within the room. It was estimated that coal combustion accounted for about 71 %, 92 %, 63 %, 59 %, and 21 % of total exposure to indoor CO₂, CO, TVOC, CH₄, and HCHO, respectively. Improved stove combined with clean fuel could effectively lower the concentrations of CO₂, CO, TVOC, and CH₄ in indoor air and reduce the contributions of coal combustion to these gaseous pollutants by about 21-68 %. These findings help better understand the indoor air pollution resulting from residential coal combustion and could guide the development of intervention programs to improve indoor air quality in rural households of northern China.

Black glucose-releasing silicon elastomer rings for fed-batch operation allow measurement of the oxygen transfer rate from the top and optical signals from the bottom for each well of a microtiter plate

BACKGROUND

In industrial microbial biotechnology, fed-batch processes are frequently used to avoid undesirable biological phenomena, such as substrate inhibition or overflow metabolism. For targeted process development, fed-batch options for small scale and high throughput are needed. One commercially available fed-batch fermentation system is the FeedPlate^®, a microtiter plate (MTP) with a polymer-based controlled release system. Despite standardisation and easy incorporation into existing MTP handling systems, FeedPlates^® cannot be used with online monitoring systems that measure optically through the transparent bottom of the plate. One such system that is broadly used in biotechnological laboratories, is the commercial BioLector. To allow for BioLector measurements, while applying the polymer-based feeding technology, positioning of polymer rings instead of polymer disks at the bottom of the well has been proposed. This strategy has a drawback: measurement requires an adjustment of the software settings of the BioLector device. This adjustment modifies the measuring position relative to the wells, so that the light path is no longer blocked by the polymer ring, but, traverses through the inner hole of the ring. This study aimed at overcoming that obstacle and allowing for measurement of fed-batch cultivations using a commercial BioLector without adjustment of the relative measurement position within each well.

RESULTS

Different polymer ring heights, colours and positions in the wells were investigated for their influence on maximum oxygen transfer capacity, mixing time and scattered light measurement. Several configurations of black polymer rings were identified that allow measurement in an unmodified, commercial BioLector, comparable to wells without rings. Fed-batch experiments with black polymer rings with two model organisms, E. coli and H. polymorpha, were conducted. The identified ring configurations allowed for successful cultivations, measuring the oxygen transfer rate and dissolved oxygen tension, pH, scattered light and fluorescence. Using the obtained online data, glucose release rates of 0.36 to 0.44 mg/h could be determined. They are comparable to formerly published data of the polymer matrix.

CONCLUSION

The final ring configurations allow for measurements of microbial fed-batch cultivations using a commercial BioLector without requiring adjustments of the instrumental measurement setup. Different ring configurations achieve similar glucose release rates. Measurements from above and below the plate are possible and comparable to measurements of wells without polymer rings. This technology enables the generation of a comprehensive process understanding and target-oriented process development for industrial fed-batch processes.

Effects of reducing, stabilizing, and antibiotic agents on "Candidatus Kuenenia stuttgartiensis"

Anaerobic ammon ium oxidizing (anammox) bacteria oxidize ammonium and reduce nitrite, producing N₂, and could play a major role in energy-optimized wastewater treatment. However, sensitivity to various environmental conditions and slow growth currently hinder their wide application. Here, we attempted to determine online the effect of environmental stresses on anammox bacteria by using an overnight batch activity test with whole cells, in which anammox activity was calculated by quantifying N₂ production via headspace-pressure monitoring. A planktonic mixed culture dominated by "Candidatus Kuenenia stuttgartiensis" strain CSTR1 was cultivated in a 30-L semi-continuous stirring tank reactor. In overnight resting-cell anammox activity tests, oxygen caused strong inhibition of anammox activity, which was reversed by sodium sulfite (30 µM). The tested antibiotics sulfamethoxazole, kanamycin, and ciprofloxacin elicited their effect on a dose-dependent manner; however, strain CSTR1 was highly resistant to sulfamethoxazole. Anammox activity was improved by activated carbon and Fe₂O₃. Protein expression analysis from resting cells after anammox activity stimulation revealed that NapC/NirT family cytochrome c (KsCSTR_12840), hydrazine synthase, hydrazine dehydrogenase, hydroxylamine oxidase, and nitrate:nitrite oxidoreductase were upregulated, while a putative hydroxylamine oxidoreductase HAO (KsCSTR_49490) was downregulated. These findings contribute to the growing knowledge on anammox bacteria physiology, eventually leading to the control of anammox bacteria growth and activity in real-world application. KEY POINTS: • Sulfite additions can reverse oxygen inhibition of the anammox process • Anammox activity was improved by activated carbon and ferric oxide • Sulfamethoxazole marginally affected anammox activity.

Assessing the capabilities of 2D fluorescence monitoring in microtiter plates with data-driven modeling for secondary substrate limitation experiments of Hansenula polymorpha

BACKGROUND

Non-invasive online fluorescence monitoring in high-throughput microbioreactors is a well-established method to accelerate early-stage bioprocess development. Recently, single-wavelength fluorescence monitoring in microtiter plates was extended to measurements of highly resolved 2D fluorescence spectra, by introducing charge-coupled device (CCD) detectors. Although introductory experiments demonstrated a high potential of the new monitoring technology, an assessment of the capabilities and limits for practical applications is yet to be provided.

RESULTS

In this study, three experimental sets introducing secondary substrate limitations of magnesium, potassium, and phosphate to cultivations of a GFP-expressing H. polymorpha strain were conducted. This increased the complexity of the spectral dynamics, which were determined by 2D fluorescence measurements. The metabolic responses upon growth limiting conditions were assessed by monitoring of the oxygen transfer rate and extensive offline sampling. Using only the spectral data, subsequently, partial least-square (PLS) regression models for the key parameters of glycerol, cell dry weight, and pH value were generated. For model calibration, spectral data of only two cultivation conditions were combined with sparse offline sampling data. Applying the models to spectral data of six cultures not used for calibration, resulted in an average relative root-mean-square error (RMSE) of prediction between 6.8 and 6.0%. Thus, while demanding only sparse offline data, the models allowed the estimation of biomass accumulation and glycerol consumption, even in the presence of more or less pronounced secondary substrate limitation.

CONCLUSION

For the secondary substrate limitation experiments of this study, the generation of data-driven models allowed a considerable reduction in sampling efforts while also providing process information for unsampled cultures. Therefore, the practical experiments of this study strongly affirm the previously claimed advantages of 2D fluorescence spectroscopy in microtiter plates.

Spotting priming-active compounds using parsley cell cultures in microtiter plates

BACKGROUND

Conventional crop protection has major drawbacks, such as developing pest and pathogen insensitivity to pesticides and low environmental compatibility. Therefore, alternative crop protection strategies are needed. One promising approach treats crops with chemical compounds that induce the primed state of enhanced defense. However, identifying priming compounds is often tedious as it requires offline sampling and analysis. High throughput screening methods for the analysis of priming-active compounds have great potential to simplify the search for such compounds. One established method to identify priming makes use of parsley cell cultures. This method relies on measurement of fluorescence of furanocoumarins in the final sample. This study demonstrates for the first time the online measurement of furanocoumarins in microtiter plates. As not all plants produce fluorescence molecules as immune response, a signal, which is not restricted to a specific plant is required, to extend online screening methods to other plant cell cultures. It was shown that the breathing activity of primed parsley cell cultures increases, compared to unprimed parsley cell cultures. The breathing activity can by monitored online. Therefore, online identification of priming-inducing compounds by recording breathing activity represents a promising, straight-forward and highly informative approach. However, so far breathing has been recorded in shake flasks which suffer from low throughput. For industrial application we here report a high-throughput, online identification method for identifying priming-inducing chemistry.

RESULTS

This study describes the development of a high-throughput screening system that enables identifying and analyzing the impact of defense priming-inducing compounds in microtiter plates. This screening system relies on the breathing activity of parsley cell cultures. The validity of measuring the breathing activity in microtiter plates to drawing conclusions regarding priming-inducing activity was demonstrated. Furthermore, for the first time, the fluorescence of the priming-active reference compound salicylic acid and of furanocoumarins were simultaneously monitored online. Dose and time studies with salicylic acid-treated parsley cell suspensions revealed a wide range of possible addition times and concentrations that cause priming. The online fluorescence measuring method was further confirmed with three additional compounds with known priming-causing activity.

CONCLUSIONS

Determining the OTR, fluorescence of the priming-active chemical compound SA and of furanocoumarins in parsley suspension cultures in MTPs by online measurement is a powerful and high-throughput tool to study possible priming compounds. It allows an in-depth screening for priming compounds and a better understanding of the priming process induced by a given substance. Evaluation of priming phenomena via OTR should also be applicable to cell suspensions of other plant species and varieties and allow screening for priming-inducing chemical compounds in intact plants. These online fluorescence methods to measure the breathing activity, furanocoumarin and SA have the potential to accelerate the search for new priming compounds and promote priming as a promising, eco-friendly crop protection strategy.

Refolding in the modern biopharmaceutical industry

Inclusion bodies (IBs) often emerge upon overexpression of recombinant proteins in E. coli. From IBs, refolding is necessary to generate the native protein that can be further purified to obtain pure and active biologicals. This work focusses on refolding as a significant process step during biopharmaceutical manufacturing with an industrial perspective. A theoretical and historical background on protein refolding gives the reader a starting point for further insights into industrial process development. Quality requirements on IBs as starting material for refolding are discussed and further economic and ecological aspects are considered with regards to buffer systems and refolding conditions. A process development roadmap shows the development of a refolding process starting from first exploratory screening rounds to scale-up and implementation in manufacturing plant. Different aspects, with a direct influence on yield, such as the selection of chemicals including pH, ionic strength, additives, etc., and other often neglected aspects, important during scale-up, such as mixing, and gas-fluid interaction, are highlighted with the use of a quality by design (QbD) approach. The benefits of simulation sciences (process simulation and computer fluid dynamics) and process analytical technology (PAT) for seamless process development are emphasized. The work concludes with an outlook on future applications of refolding and highlights open research inquiries.

Screening of early warning indicators for full-scale dry anaerobic digestion of household kitchen waste

Process monitoring is an essential measure to achieve efficient and stable performance in anaerobic digestion, thus requiring identification of effective early warning indicators. However, the application of early warning indicators to full-scale dry anaerobic engineering biogas plant still remains elusive. This study evaluated the effectiveness of common early warning indicators (including CH₄, CO₂, H₂S, volatile fatty acids (VFAs), alkalinity (ALK), total ammonia concentration (TAN) and free ammonia concentration (FAN)) in monitoring the instability of anaerobic digestion process at a practical engineering plant. The results showed that the individual indicators could not provide a sufficient early warning time before the digester fell into failure collapse. In comparison, the coupling indicators (the ratio of CH₄/CO₂, CH₄/pH, and CH₄/H₂S) had sensitive response to perturbation, which could regard as a potential early warning indicator, with the early warning time of 6, 7 and 10 days, respectively. Moreover, the VFA/ALK could be used as auxiliary indicators due to the limitation of complex detection methods. In addition, the result also indicated that the application of some warning indicators needs to be further verified, when transferring the result of laboratory scale to the practice application scenarios. This study provides insight into the stable operation of dry anaerobic engineering.

Online colloidal particle monitoring for controlled coagulation pretreatment to lower microfiltration membrane fouling at a potable water reuse facility

Fouling of microfiltration (MF)) membranes during water/wastewater treatment is predominantly caused by colloidal particles (size <1 µm) in the feed water. Until recently no online technology was available to directly measure the occurrence of colloidal particles in these waters. This study evaluated the viability of a novel online light scattering technology (Nanoparticle Tracking Analysis) to continuously monitor colloidal particles in the membrane feed water (a secondary-treated wastewater) for targeted removal by injecting coagulant at a dosage proportional to the measured concentration of colloidal particles. A diurnal variation was observed in the colloidal particle concentration in the feed water with the lowest concentration occurring at approximately 6 am and the highest concentration occurring after mid-day. The peak colloidal particle concentrations were 4 to 6 times higher than the lowest concentrations measured on the same day. Bench-scale studies were performed to develop a relationship between colloidal particle concentration and the optimum coagulant dosage required for their removal. Subsequently, a pilot-scale study was performed using two MF pilot units operated in parallel, one receiving targeted coagulant dosing and the other with no coagulant dosing, to demonstrate the effectiveness of targeted coagulant dosing in preventing membrane fouling. The pilot unit that received targeted coagulant dose experienced only 4 to 20% of the transmembrane pressure increase of the increase experienced by the pilot unit that received no coagulant. Evaluation of fouling resistance indicated that targeted coagulation improved flux by predominantly lowering the irreversible fouling. The filtrate water quality measured by colloidal particle concentration, chemical oxygen demand (COD), and turbidity were very similar for the two pilot units. This suggests that although the efficiency of particle and organic materials removal does not change with coagulant addition, the particles filtered by the membrane in the control unit contributed to membrane irreversible fouling, while in the coagulant-treated unit, the coagulated colloidal particles were removed away from the membrane into the backwash stream during the frequent backwash/air scour procedures.

An online technology for effectively monitoring inorganic condensable particulate matter emitted from industrial plants

The concentration of condensable particulate matter (CPM) has gradually exceeded that of filterable particulate matter emitted from industrial plants equipped with advanced air pollution control systems. However, there is still no available online technology to measure CPM emissions. Based on the significant linear correlations (R² > 0.87, p < 3 × 10^-3) between the electrical conductivity (EC) values and ionic mass concentrations of the CPM solutions when the interference of H⁺ was excluded. We developed an online inorganic CPM monitoring system, including a cooling and condensation unit, pH and EC meters, a self-cleaning unit, and an automatic control unit. The CPM mass concentrations obtained by the developed online monitoring system agree well (mean bias 3.8-20.7%) with those obtained by the offline system according to USEPA Method 202 when used in parallel during real-world studies. Furthermore, individual ion mass concentrations of CPMs can even be retrieved separately with a time resolution of one hour when industrial plants are under steady operating conditions. The newly developed system makes the online monitoring of CPM emissions available and lays a foundation for the control of CPM emitted from industrial sources to further improve air quality.

Model-based mid-infrared spectroscopy for on-line monitoring of volatile fatty acids in the anaerobic digester

The performance of anaerobic digestion is significantly governed by the concentration of volatile fatty acids (VFAs). Though the titration and near-infrared spectroscopy have been used to measure the VFAs in the digester, there is still lack of the establishment of on-line monitoring of VFAs in practical application. An effective quantification method based on mid-infrared (MIR) spectroscopy was developed, and used to measure the concentrations of VFAs in the anaerobic bioreactor nondestructively in parallel. The wavelet denoising (WD) spectra were used as the spectral preprocessing option. Compared with other pretreatment methods, the established calibration model built by WD spectra showed satisfactory results. Further, the model was verified using high performance liquid chromatography (HPLC), and predictions were made using real reactor effluent samples. Based on this theoretical work, a set of equipment for the in-situ online monitoring of VFAs was designed, which has high feasibility and effectively solves the problems with the current VFAs online monitoring process. These results provide a new solution for on-line monitoring of the anaerobic digestion, and have great potential for practical application.

Online evaluation of bacterial cells in sand filter effluents during full-scale treatment of drinking water

Ensuring the microbiological safety of drinking water is critical to protect public health. This study aimed to evaluate the reliability of real-time bacteriological counter coupled with an online dialysis membrane-based pre-treatment system for continuously monitoring bacterial cell counts in sand filter effluents of a full-scale drinking water treatment plant. The pre-treatment system, which included anion exchange resins (porous polymeric microbeads that trap ions for releasing other ions) for dialysate regeneration, successfully achieved the stable attenuation of background interfering substances (humic acids) during the 19-d test. The real-time bacteriological counter equipped with the pre-treatment system provided a continuous profile of bacterial cell counts in the sand filter effluent (0.2-2.5 × 10⁴ counts/mL). The online analysis identified different timing of concentration peaks between particle and bacterial cell counts after backwashing. Bacterial community analysis revealed that Proteobacteria, Planctomycetes, and Cyanobacteria were the dominating phyla. Further, total bacterial cell counts determined by fluorescence microscopy and SYBR® Green I staining, a commonly accepted parameter, was found to be an indicator of online-monitored bacterial cell counts. The results indicated the potential of monitoring the bacterial cell counts in a sand filter process for providing an early warning of filter failures, which can allow plant operators to diagnose the overall system and provide countermeasures.

3D printed microfluidic mixer for real-time monitoring of organic reactions by direct infusion mass spectrometry

3D printing is a technology that has revolutionized traditional rapid prototyping methods due to its ability to build microscale structures with customized geometries in a simple, fast, and low-cost way. In this sense, this article describes the development of a microfluidic mixing device to monitor chemical reactions by mass spectrometry (MS). Microfluidic mixers were designed containing 3D serpentine and Y-shaped microchannels, both with a pointed end for facilitating the spray formation. The devices were fabricated entirely by 3D printing with fusion deposition modeling (FDM) technology. As proof-of-concept, micromixers were evaluated through monitoring the Katritzky reaction by injecting simultaneously 2,4,6-triphenylpropyllium (TPP) and amino acid (glycine or alanine) solutions, each through a different reactor inlet. Reaction product was monitored online by MS at different flow rates. Mass spectra showed that the relative abundances of the products obtained with the device containing the 3D serpentine channel were three times greater than those obtained with the Y-channel device due to the turbulence generated by the barriers created inside microchannels. In addition, when compared to the conventional electrospray ionization mass spectrometry (ESI-MS) technique, the 3D serpentine mixer offered better performance measured in relation to the relative abundance values for the reaction products. These results as well as the instrumental simplicity indicate that 3D printed microfluidic mixer is a promising tool for monitoring organic reactions via MS.

The iSplit GFP assay detects intracellular recombinant proteins in Bacillus subtilis

BACKGROUND

Bacillus subtilis is one of the most important microorganisms for recombinant protein production. It possesses the GRAS (generally recognized as safe) status and a potent protein secretion capacity. Secretory protein production greatly facilitates downstream processing and thus significantly reduces costs. However, not all heterologous proteins are secreted and intracellular production poses difficulties for quantification. To tackle this problem, we have established a so-called intracellular split GFP (iSplit GFP) assay in B. subtilis as a tool for the in vivo protein detection during expression in batch cultures and at a single-cell level. For the iSplit GFP assay, the eleventh β-sheet of sfGFP is fused to a target protein and can complement a detector protein consisting of the respective truncated sfGFP (GFP1-10) to form fluorescent holo-GFP.

RESULTS

As proof of concept, the GFP11-tag was fused C-terminally to the E. coli β-glucuronidase GUS, resulting in fusion protein GUS11. Variable GUS and GUS11 production levels in B. subtilis were achieved by varying the ribosome binding site via spacers of increasing lengths (4-12 nucleotides) for the GUS-encoding gene. Differences in intracellular enzyme accumulation were determined by measuring the GUS11 enzymatic activity and subsequently by adding the detector protein to respective cell extracts. Moreover, the detector protein was co-produced with the GUS11 using a two-plasmid system, which enabled the in vivo detection and online monitoring of glucuronidase production. Using this system in combination with flow cytometry and microfluidics, we were able to monitor protein production at a single-cell level thus yielding information about intracellular protein distribution and culture heterogeneity.

CONCLUSION

Our results demonstrate that the iSplit GFP assay is suitable for the detection, quantification and online monitoring of recombinant protein production in B. subtilis during cultivation as well as for analyzing production heterogeneity and intracellular localization at a single-cell level.

Electrical impedance spectroscopy as a potential tool to investigate the structure and size of aggregates during water and wastewater treatment

Microscopic structure and size are important metrics for estimating aggregates environmental behaviors during water and wastewater treatment. However, in-situ determination of these characteristics is still a challenge. Here, we drew inspiration from a block disassembly process to propose an electrical impedance spectroscopy (EIS) method and constructed a generalized framework to associate macroscale electrical properties with microscopic structure and size-related characteristics of aggregates of different hierarchies. Extracted via EIS, the proposed models were verified to be capable of describing the self-similarity of aggregates and capturing the fractal and size information. Further, the proposed models exhibited a wide range of applications, which agrees well with the data gathered from various activated sludges, other colloids, and microgels in water and wastewater treatment. Finally, the EIS method was achieved online monitoring of fractal dimension and floc size during a sludge pre-oxidation conditioning process, which was elected as an example to illustrate the potential online applications of this EIS method in real water and wastewater environment. The obtained on-line data were used to indicate the potential suitable oxidation time during sludge pre-oxidation conditioning. These observations may inspire new methods of quantifying the aggregate structure and promote intelligent and dynamic decision-making during water and wastewater treatment.

Online monitoring of lead-214 (214Pb) on atmospheric aerosols by low-resolution gamma-ray spectrometry

This paper provides a new approach that simplifies the monitoring of ²¹⁴Pb activity concentration on aerosols in the atmospheric surface layer. The approach allows obtaining data on ²¹⁴Pb activity concentration with the discreteness of 2 h. The experimental setup described in the paper made it possible to achieve a minimum detectable activity level of 0.4 Bq m^-3. Using this approach, the data on the diurnal variability of ²¹⁴Pb activity concentration in the atmosphere of Sevastopol city for a period of 18 months were obtained. The ²¹⁴Pb activity concentration varied from < 0.4 (less than 1% of the data series) to 8.9 Bq m^-3, mean value 2.0 ± 1.0 Bq m^-3. The analysis of the temporal variability of ²¹⁴Pb activity concentration on different time scales (diurnal, seasonal) was carried out. Annually averaged diurnal variation curve of ²¹⁴Pb activity concentration showed a peak at 6:00 local time and a minimum at 18:00. The maximum variability in the seasonal averaged diurnal cycle of ²¹⁴Pb activity concentration is observed in summer (± 30% of the daily average value) and the minimum in winter (± 13%). The maximum seasonal average value of ²¹⁴Pb activity concentration is observed in winter (2.5 Bq m^-3) and the minimum in summer (1.4 Bq m^-3). A quantitative estimate of the annual effective dose due to exposure to outdoor radon was obtained by using ²¹⁴Pb data, and it was 0.03 mSv a^-1.

Simulating chlorophyll-a fluorescence changing rate and phycocyanin fluorescence by using a multi-sensor system in Lake Taihu, China

Algal pollution in water sources has posed a serious problem. Estimating algal concentration in advance saves time for drinking water plants to take measures and helps us to understand causal chains of algal dynamics. This paper explores the possibility of building a short-term algal early warning model with online monitoring systems. In this study, we collected high-frequency data for water quality and weather conditions in shallow and eutrophic Lake Taihu by an in situ multi-sensor system (BIOLIFT) combined with a weather station. Extracted chlorophyll-a from water samples and chlorophyll-a fluorescence differentiated according to different algal classeses verified that chlorophyll-a fluorescence continuously measured by BIOLIFT only represent chlorophyll-a of green algae and diatoms. Stepwise linear regression was used to simulate the chlorophyll-a fluorescence changing rate of green algae and diatoms together (ΔChl_a-f%) and phycocyanin fluorescence concentration (blue-green algae) on the water surface layer (CyanoS). The results show that nutrients (total N, NO₃-N, NH₄-N, total P) were not necessary parameters for short-term algal models. ΔChl_a-f % is greatly influenced by the seasons, so seasonal partition of data before modeling is highly recommended. CyanoS_max and ΔChl_a-f% were simulated by only using multi-sensor and meteorological data (R² = 0.73; 0.75). All the independent variables (wave, water temperature, relative humidity, depth, cloud cover) used in the model were measured online and predictable. Wave height is the most important independent variable in the shallow lake. This paper offers a new approach to simulate and predict the algal dynamics, which also can be applied in other surface water.

Reusable, facile, and rapid aptasensor capable of online determination of trace mercury

Herein, we reported a homemade waveguide-based evanescent wave aptasensor for the facile online monitoring of mercury pollution. The aptasensor exploited the high selectivity of hairpin structure-based thymidine-Hg²⁺-thymidine coordination chemistry (T-T mismatch) for Hg²⁺ recognition and the stably regenerable capability of DNA-functionalized waveguide surfaces. The presence of Hg²⁺ caused the T-T mismatch of Cy5.5-labeled T-rich single-stranded DNA sequences. The formed hairpin structures blocked the further hybridization of T-rich single-stranded DNA sequences with the complementary DNA strands that are modified on the waveguide surface; this phenomenon was accompanied by the decrease in the fluorescent signals excited by the evanescent wave. The limit of detection in real water samples was determined to be 0.2 μg/L, which was comparable with that of 0.4 μg/L in an ultrapure water under controlled conditions. And the linear range was observed from 1.4 µg/L to 240.7 µg/L. The negligible environmental matrix effect on the performance ensured the reliability of the proposed aptasensor. Moreover, the cross reactivity of this method toward other investigated metal ions was negligible. Through the delicate surface modification with DNA molecules covalently, the chip was reused at least 31 times with a relative standard deviation (RSD) of less than 19%. A Hg²⁺ pollution accident was successfully detected within 30 min, shedding new light in pollution monitoring, environment restoration, and emergency treatment.

Simultaneous absorption of UV-vis and circular dichroism to measure enantiomeric concentrations of praziquantel under nonlinear conditions

Beer-Lambert-Bouguer law is for a limiting case and, therefore, it is not useful to describe the relationship between absorption signal and enantiomer concentration in a stream when there are nonlinear phenomena present. In this work, the Chiral Detector (CD-2095 JASCO) equipment was used to measure simultaneously the UV-Vis and circular dichroism (CD) signals of a stream with different compositions of praziquantel enantiomers. The tested models were calibrated (parameter estimation) and validated using the Leave-One-Out Cross Validation (LOOCV) method. Both UV-vis and CD signals were absorbed differently in mixtures in comparison to pure solutions, indicating a nonlinear relationship between the absorbed signal and the enantiomer concentration in a mixture stream. Empirical mathematical relationships were tested for each signal (UV-vis and CD) and the pair of equations was evaluated using the Mean Square Error (MSE) metric for each enantiomer concentration (MSE_L and MSE_D) and the pair of equations with the smallest MSE_t (=MSE_L + MSE_D) metric was chosen. Confidence interval analysis helped to find even simpler equations in comparison to the chosen ones. Higher nonlinearity was observed for a mixture with low L-PZQ concentration. The developed methodology allowed the choice of an empiric model to give good predictions in a wide range of concentration, what is of utmost importance for monitoring and automatic control purposes, for instance.

Optical ammonia sensors based on fluorescent aza-BODIPY dyes- a flexible toolbox

We present three types of optical ammonia sensors suitable for environmental, bioprocess, and reaction monitoring. A respective fluorescent BF2-chelated tetraarylazadipyrromethene dye (aza-BODIPYs) is physically entrapped in a polyurethane hydrogel (HydroMed D4) forming an emulsion system with vinyl-terminated polydimethylsiloxane (PDMS). The analyte-sensitive layer is covered by a hydrophobic membrane which excludes hydrophilic substances. Three different protection layers are tested, whereby the Teflon and the hydrophobic PES layers outperform a PDMS/TiO2 layer. Response times within their dynamic range of 15 s can be achieved, whereas the PDMS/TiO2-covered sensor requires at least 390 s. The three sensors entail the following concentration areas: first sensor 3 μg L-1-3 mg L-1 (LOD 0.23 μg L-1), second sensor 0.1-30 mg L-1 (LOD 28 μg L-1), and third sensor 3 mg L-1-1 g L-1 (LOD 0.51 mg L-1). Readout is performed with a commercially available phase fluorimeter combined with optical fibers. Dual-lifetime referencing (DLR) is used as referencing method and Egyptian blue acts as an inert reference material. No cross-sensitivity to pH changes can be detected.

Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China

The chemical species in PM_2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM_2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM_2.5 was 124 μg/m³ during the heating period, and NO₃^- and organic carbon (OC) were the dominant species. The concentrations and percentages of NO₃^-, SO₄^2-, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM_2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.

Monitoring yeast fermentations by nonlinear infrared technology and chemometrics-understanding process correlations and indirect predictions

Fermentation processes are still compromised by a lack of monitoring strategies providing integrated process data online, ensuring process understanding, control, and thus, optimal reactor efficiency. The crucial demand for online monitoring strategies, not only encouraged by the PAT initiative but also motivated by modern paradigms such as circular economy and sustainability, has driven research and industry to provide "next-generation process technology": in other words, technology tailored toward industrial needs. Mid-infrared (MIR) spectroscopy as such is superior to near-infrared (NIR) spectroscopy since it provides significantly enhanced selectivity. However, due to high costs and a lack of instrumental robustness, MIR spectroscopy is outcompeted by NIR when it comes to industrial application. The lack of chemometric expertise, model understanding, and practical guidance might add to the slow acceptance of industrial MIR application. This work demonstrates the use of novel MIR, so-called non-linear infrared (NLIR) technology and the importance of model understanding, exemplarily investigated on a lab-scale yeast fermentation process. The six analytes glucose, ethanol, glycerol, acetate, ammonium, and phosphate were modeled by partial least squares (PLS) based on spectral data, demonstrating the potential of the novel technology facilitating online data acquisition and the necessity of investigating indirect predictions. KEY POINTS: • NLIR spectra were acquired online during a yeast fermentation process • PLS models were constructed for six components based on uncorrelated samples • Glucose, ethanol, ammonium, and phosphates were modeled with errors of less than 15% • Acetate and glycerol were shown to rely on indirect predictions.

Detailed small-scale characterization and scale-up of active YFP inclusion body production with Escherichia coli induced by a tetrameric coiled coil domain

During heterologous protein production with Escherichia coli, the formation of inclusion bodies (IBs) is often a major drawback as these aggregated proteins are usually inactive. However, different strategies for the generation of IBs consisting of catalytically active proteins have recently been described. In this study, the archaeal tetrameric coiled-coil domain of the cell-surface protein tetrabrachion was fused to a target reporter protein to produce fluorescent IBs (FIBs). As the cultivation conditions severely influence IB formation, the entire cultivation process resulting in the production of FIBs were thoroughly studied. First, the cultivation process was scaled down based on the maximum oxygen transfer capacity, combining online monitoring technologies for shake flasks and microtiter plates with offline sampling. The evaluation of culture conditions in complex terrific broth autoinduction medium showed strong oxygen limitation and leaky expression. Furthermore, strong acetate formation and pH changes from 6.5 to 8.8 led to sub-optimal cultivation conditions. However, in minimal Wilms-MOPS autoinduction medium, defined culture conditions and a tightly controlled expression were achieved. The production of FIBs is strongly influenced by the induction strength. Increasing induction strengths result in lower total amounts of functional protein. However, the amount of functional FIBs increases. Furthermore, to prevent the formation of conventional inactive IBs, a temperature shift from 37 °C to 15 °C is crucial to generate FIBs. Finally, the gained insights were transferred to a stirred tank reactor batch fermentation. Hereby, 12 g/L FIBs were produced, making up 43 % (w/w) of the total generated biomass.

Propagation characteristics of ultrasonic weld-guided waves in Friction stir welding joint of same material

Friction stir welding (FSW) is an important technology for manufacturing large-scale aluminum alloy propellant tank. Due to stress corrosion and cyclic loads, the key FSW joints require online monitoring to ensure the structural integrity and service safety of long-term storage propellant tanks. FSW joints in the propellant tank are regarded as a type of circumferential or longitudinal long and narrow region. In order to detect the flaws with high efficiency and fewer sensors, the propagation characteristics of ultrasonic guided waves in the FSW joint of same material is investigated in this paper. The weld of a FSW joint is characterized by concave cross-sectional shape and different microstructure-mechanical parameters. The micro-structure, micro-hardness, and Young's modulus of a real FSW joint are analyzed, and a two-dimensional semi-analytical finite-element (SAFE) method is employed to study the effects of different parameters on the modal characteristics of weld-guided waves in the FSW joint. In the studied fundamental modes (symmetric (S0), anti-symmetric (A0), and shear-horizontal (SH0)), an almost non-leaky A0-like weld-guided wave at a certain frequency range from 100 kHz to 210 kHz is discovered in the welded zone of a specific FSW model and shows a potential for long-distance detection. Parametric simulation results show that A0-like, SH0-like and S0-like modes at 120 kHz always exist when the weld width is changed while the moduli of the welded zone and base metal zone are maintained the same. Additionally, the simulations demonstrate that some weld-guided waves only exist if the modulus value of the welded zone is lower than that of the base metal zone when the cross section is geometrically continuous (i.e. the shoulder plunge depth is zero). Comparing with weld-guided waves affected by weld width, the weld-guided waves affected by the modulus change shows less obvious energy leakage during propagation. The experiments are conducted to validate the existence of A0-like weld-guided mode with a primary energy trapping effect.

FT-RAMAN methodology for the monitoring of honeys' spirit distillation process

Honey spirit is an alcoholic beverage produced by fermentation followed by distillation of the honey must, which has distinct organoleptic characteristics derived mostly from the raw material used. In order to accurately monitor the quality of the product throughout the distillation process (head, heart and tail stages), FT-RAMAN spectroscopy was applied. Dark honey, light honey and honey obtained following waxes' wash was used to produce honey spirit. The pH, alcoholic strength, methanol content, acetaldehyde content, ethyl acetate content and higher alcohols content were evaluated during the distillation process. The FT-RAMAN technique was used to obtain spectral information for all fractions collected during beverage production. The results suggest that the honey spirit had good quality concerning the volatile composition and methanol was not detected in any sample. FT-RAMAN is promising for the online monitoring of the distillation process in order to improve the final quality of this beverage.

Potential effects of internal physio-ecological changes on the online biomonitoring of water quality: The behavior responses with circadian rhythms of zebrafish (Danio rerio) to different chemicals

The online biomonitoring of aquatic accidental pollution is very important to realize the assessment of complex toxicity. However, the monitoring results would be affected greatly by the internal physio-ecological changes of test organisms, and circadian rhythms might contribute greatly to this kind of effects. In the present study, the behavior responses of zebrafish (Danio rerio) to different concentrations of Deltamethrin, Atrazine, and Thallium (Tl) in 15 days were investigated using an online behavior monitoring system. The results showed that the average behavior strength (BS) value of dark period (0.71 ± 0.16) was lower than that of light period (0.88 ± 0.09) in the control group. Similar pattern was observed in all other treatments with negative relationship between exposure concentrations and mean BS values. It is concluded that the 24 h circadian rhythms in the behavior responses of zebrafish (Danio rerio) could be observed clearly in the online biomonitoring system, and the online monitoring results would be affected obviously in the characteristics of behavior periodicity abnormal and time delay. Therefore, it is suggested that internal physio-ecological characteristics of organisms must be considered once they have the chance to play roles in bio-induced technologies. More investigations are warranted to clear the effects of internal physio-ecological changes on the exported results.

Conductometric sensor for viable Escherichia coli and Staphylococcus aureus based on magnetic analyte separation via aptamer

A method is described to determine viable populations of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The method employs aptamer-magnetic separation combined with resistivity based detection. The bacteria were separated by means of aptamer-functionalized magnetic beads. They were then quantified by measuring their growth kinetics through time-dependent conductivity changes of culture media. The time-course of growth was logged by real-time and contactless measurements that yielded starting concentrations from the duration of lag intervals prior to the log phase of growth. In pure water samples, the linear ranges for measuring E. coli and S. aureus cells are 2.5 × 10³-2.5 × 10⁸ CFU·mL^-1 and 4.1 × 10³-4.1 × 10⁸ CFU·mL^-1, respectively. In spiked tap water samples, the lower limits of detection are 2.3 × 10⁴ CFU·mL^-1 and 4.0 × 10³ CFU·mL^-1 for E. coli and S. aureus, with recoveries of 87.0-108.7% and 92.5-105.0%, respectively. The relative standard deviation of these measurements (10.0%) is below that of plate counting method (13.9%). The presence of micro/nanoparticles such as magnetic beads or selenium nanoparticles in the culture media does not interfere, unlike in case of automatted optical density monitoring. The E. coli and S. aureus cells captured on the aptamer-functionalized magnetic beads can be directly tested for their susceptibility to antibiotics. The process of magnetic separation and determination of load burden requires neither bulky, sophisticated equipment nor expensive reagents. Graphical abstractAptamer-functionalized magnetic beads are used to selectively capture and separate E. coli and S. aureus cells in aqueous samples. They are directly transferred to a multichannel conductometric sensor for the quantification of viable bacteria via automated monitoring of their growth kinetics.

Tracking the contribution of multiple raw and treated wastewater discharges at an urban drinking water supply using near real-time monitoring of β-d-glucuronidase activity

Past waterborne outbreaks have demonstrated that informed vulnerability assessment of drinking water supplies is paramount for the provision of safe drinking water. Although current monitoring frameworks are not designed to account for short-term peak concentrations of fecal microorganisms in source waters, the recent development of online microbial monitoring technologies is expected to fill this knowledge gap. In this study, online near real-time monitoring of β-d-glucuronidase (GLUC) activity was conducted for 1.5 years at an urban drinking water intake impacted by multiple point sources of fecal pollution. Parallel routine and event-based monitoring of E. coli and online measurement of physico-chemistry were performed at the intake and their dynamics compared over time. GLUC activity fluctuations ranged from seasonal to hourly time scales. All peak contamination episodes occurred between late fall and early spring following intense rainfall and/or snowmelt. In the absence of rainfall, recurrent daily fluctuations in GLUC activity and culturable E. coli were observed at the intake, a pattern otherwise ignored by regulatory monitoring. Cross-correlation analysis of time series retrieved from the drinking water intake and an upstream Water Resource Recovery Facility (WRRF) demonstrated a hydraulic connection between the two sites. Sewage by-passes from the same WRRF were the main drivers of intermittent GLUC activity and E. coli peaks at the drinking water intake following intense precipitation and/or snowmelt. Near real-time monitoring of fecal pollution through GLUC activity enabled a thorough characterization of the frequency, duration and amplitude of peak contamination periods at the urban drinking water intake while providing crucial information for the identification of the dominant upstream fecal pollution sources. To the best of our knowledge, this is the first characterization of a hydraulic connection between a WRRF and a downstream drinking water intake across hourly to seasonal timescales using high frequency microbial monitoring data. Ultimately, this should help improve source water protection through catchment mitigation actions, especially in a context of de facto wastewater reuse.

Polymer-based ammonium-limited fed-batch cultivation in shake flasks improves lipid productivity of the microalga Chlorella vulgaris

The aim of this work was to study ammonium-limited fed-batch conditions in heterotrophic C. vulgaris shake flask cultivations. Therefore, an innovative polymer-based ammonium release technique (polymer beads) was developed. Using these beads in shake flasks, C. vulgaris cultivations resulted in simultaneous growth and lipid accumulation. Lipid productivity was increased by 43% compared to batch cultivations. Furthermore, by online monitoring of the metabolic activity (RAMOS technique), unlimited growth and depletion of nutrients could be identified. A previously unknown sulfur limitation was detected in the applied Bold's Basal Medium. Combining the ammonium release beads with the RAMOS technique proved to be an efficient method for microalgae process development.

FeedER: a feedback-regulated enzyme-based slow-release system for fed-batch cultivation in microtiter plates

With the advent of modern genetic engineering methods, microcultivation systems have become increasingly important tools for accelerated strain phenotyping and bioprocess engineering. While these systems offer sophisticated capabilities to screen batch processes, they lack the ability to realize fed-batch processes, which are used more frequently in industrial bioprocessing. In this study, a novel approach to realize a feedback-regulated enzyme-based slow-release system (FeedER), allowing exponential fed-batch for microscale cultivations, was realized by extending our existing Mini Pilot Plant technology with a customized process control system. By continuously comparing the experimental growth rates with predefined set points, the automated dosage of Amyloglucosidase enzyme for the cleavage of dextrin polymers into d-glucose monomers is triggered. As a prerequisite for stable fed-batch operation, a constant pH is maintained by automated addition of ammonium hydroxide. We show the successful application of FeedER to study fed-batch growth of different industrial model organisms including Corynebacterium glutamicum, Pichia pastoris, and Escherichia coli. Moreover, the comparative analysis of a C. glutamicum GFP producer strain, cultivated under microscale batch and fed-batch conditions, revealed two times higher product yields under slow growing fed-batch operation. In summary, FeedER enables to run 48 parallel fed-batch experiments in an automated and miniaturized manner, and thereby accelerates industrial bioprocess development at the screening stage.

A closer look at Aspergillus: online monitoring via scattered light enables reproducible phenotyping

BACKGROUND

Filamentously growing microorganisms offer unique advantages for biotechnological processes, such as extraordinary secretion capacities, going along with multiple obstacles due to their complex morphology. However, limited experimental throughput in bioprocess development still hampers taking advantage of their full potential. Miniaturization and automation are powerful tools to accelerate bioprocess development, but so far the application of such technologies has mainly been focused on non-filamentous systems. During cultivation, filamentous fungi can undergo remarkable morphological changes, creating challenging cultivation conditions. Depending on the process and product, only one specific state of morphology may be advantageous to achieve e.g. optimal productivity or yield. Different approaches to control morphology have been investigated, such as microparticle enhanced cultivation. However, the addition of solid microparticles impedes the optical measurements typically used by microbioreactor systems and thus alternatives are needed.

RESULTS

Aspergillus giganteus IfGB 0902 was used as a model system to develop a time-efficient and robust workflow allowing microscale cultivation with increased throughput. The effect of microtiter plate geometry, shaking frequency and medium additives (talc and calcium chloride) on homogeneity of culture morphology as well as reproducibility were analyzed via online biomass measurement, microscopic imaging and cell dry weight. While addition of talc severely affected online measurements, 2% (w v-1) calcium chloride was successfully applied to obtain a highly reproducible growth behavior with homogenous morphology. Furthermore, the influence of small amounts of complex components was investigated for the applied model strain. By correlation to cell dry weight, it could be shown that optical measurements are a suitable signal for biomass concentration. However, each correlation is only applicable for a specific set of cultivation parameters. These optimized conditions were used in micro as well as lab-scale bioreactor cultivation in order to verify the reproducibility and scalability of the setup.

CONCLUSION

A robust workflow for A. giganteus was developed, allowing for reproducible microscale cultivation with online monitoring, where calcium chloride is an useful alternative to microparticle enhanced cultivation in order to control the morphology. Independent of the cultivation volume, comparable phenotypes were observed in microtiter plates and in lab-scale bioreactor.

Online assessment of sand filter performance for bacterial removal in a full-scale drinking water treatment plant

Microbiological risks associated with drinking water can be minimized by providing enhanced integrity monitoring of bacterial removal by water treatment processes. This study aimed to evaluate the efficacy of real-time bacteriological counters for continuously assessing the performance of a full-scale sand filter to remove bacteria. Over the course of an 8-day evaluation, online counting of bacteria was successfully performed, providing continuous bacterial counts in the sand filter influent and effluent over approximate ranges from 17 × 10⁴ to 94 × 10⁴ and from 0.2 × 10⁴ to 1.3 × 10⁴ counts/mL, respectively. Periodic variations were observed with online bacterial counts in the sand filter influent because of the changes in the performance of flocculation and sedimentation processes. Overall, online removal rates of bacteria determined during the full-scale test were 95.2-99.3% (i.e., 1.3-2.2-log), indicating that online bacterial counting can continuously demonstrate over 1.3-log removal in the sand filter. Real-time bacteriological counting technology can be a useful tool for assessing variability and detecting bacterial breakthrough. It can be integrated with other online water quality measurements to evaluate underlying trends and the performance of sand filters for bacterial removal, which can enhance the safety of drinking water.

Shake flask methodology for assessing the influence of the maximum oxygen transfer capacity on 2,3-butanediol production

BACKGROUND

Production of 2,3-butanediol from renewable resources is a promising measure to decrease the consumption of fossil resources in the chemical industry. One of the most influential parameters on biotechnological 2,3-butanediol production is the oxygen availability during the cultivation. As 2,3-butanediol is produced under microaerobic process conditions, a well-controlled oxygen supply is the key parameter to control biomass formation and 2,3-butanediol production. As biomass is on the one hand not the final product, but on the other hand the essential biocatalyst, the optimal compromise between biomass formation and 2,3-butanediol production has to be defined.

RESULTS

A shake flask methodology is presented to evaluate the effects of oxygen availability on 2,3-butanediol production with Bacillus licheniformis DSM 8785 by variation of the filling volume. A defined two-stage cultivation strategy was developed to investigate the metabolic response to different defined maximum oxygen transfer capacities at equal initial growth conditions. The respiratory quotient was measured online to determine the point of glucose depletion, as 2,3-butanediol is consumed afterwards. Based on this strategy, comparable results to stirred tank reactors were achieved. The highest space-time yield (1.3 g/L/h) and a 2,3-butanediol concentration of 68 g/L combined with low acetoin concentrations and avoided glycerol formation were achieved at a maximum oxygen transfer capacity of 13 mmol/L/h. The highest overall 2,3-butanediol concentration of 78 g/L was observed at a maximum oxygen transfer capacity of 4 mmol/L/h.

CONCLUSIONS

The presented shake flask approach reduces the experimental effort and costs providing a fast and reliable methodology to investigate the effects of oxygen availability. This can be applied especially on product and by-product formation under microaerobic conditions. Utilization of the maximum oxygen transfer capacity as measure for the oxygen availability allows for an easy adaption to other bioreactor setups and scales.

Autonomous online measurement of β-D-glucuronidase activity in surface water: is it suitable for rapid E. coli monitoring?

Microbiological water quality is traditionally assessed using culture-based enumeration of faecal indicator bacteria such as Escherichia coli. Despite their relative ease of use, these methods require a minimal 18-24 h-incubation step before the results are obtained. This study aimed to assess the suitability of an autonomous online fluorescence-based technology measuring β-glucuronidase (GLUC) activity for rapid near-real time monitoring of E. coli in water. The analytical precision was determined and compared to an automated microbial detection system, two culture-based assays and quantitative real-time PCR (qPCR). Using replicate measurements of grab samples containing E. coli concentrations between 50 and 2330 CFU.100 mL^-1, the autonomous GLUC activity measurement technology displayed an average coefficient of variation (CV) of less than 5% that was 4-8-fold lower than other methods tested. Comparable precision was observed during online in situ monitoring of GLUC activity at a drinking water intake using three independent instruments. GLUC activity measurements were not affected by sewage or sediments at concentrations likely to be encountered during long-term monitoring. Furthermore, significant (p < 0.05) correlations were obtained between GLUC activity and the other assays including defined substrate technology (r = 0.77), membrane filtration (r = 0.73), qPCR (r = 0.55) and the automated microbial detection system (r = 0.50). This study is the first to thoroughly compare the analytical performance of rapid automated detection technologies to established culture and molecular-based methods. Results show that further research is required to correlate GLUC activity to the presence of viable E. coli as measured in terms of CFU.100 mL^-1. This would allow the use of autonomous online GLUC activity measurements for rapid E. coli monitoring in water supplies used for drinking water production and recreation.