Evaluation of fluorescent dyes to measure protein aggregation within mammalian cell culture supernatants

BACKGROUND

A current challenge in bioprocessing is the ability to analyse critical quality attributes such as aggregation without prior purification. This study evaluated the use of fluorescent dyes (Bis‐ANS, SYPRO Orange, Thioflavin T and ProteoStat) to characterise mAb aggregates in Chinese hamster ovary clarified cultures.

RESULTS

The null and mAb culture supernatants showed an increase in fluorescence intensity over the duration of the culture. The null cultures on day 14 saw a rapid increase in fluorescence intensity; day 10 to day 14, Bis‐ANS and Thioflavin T had average increases of 21% and 48%, respectively, whereas ProteoStat and SYPRO Orange showed an average increase of 60%. Higher fluorescence intensity on day 14 with the null cultures, also correlated with loss of viability.

CONCLUSION

Fluorescent dyes are not a specific indicator of mAb aggregation, but rather an indicator of overall protein aggregation or high molecular weight species. SYPRO Orange was more sensitive at detecting very large molecular weight species and ProteoStat seemed better suited to smaller aggregates. Although the assay cannot be used to measure mAb aggregates in cell culture, it could be used to aid cell line selection in maximising viabilities and minimising the amount of aggregates. © 2017 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Towards clinical applications of selected reaction monitoring for plasma protein biomarker studies

The widespread clinical adoption of protein biomarkers with diagnostic, prognostic and/or predictive value remains a formidable challenge for the biomedical community. From discovery to validation, the path to biomarkers of clinical relevance abounds with many protein candidates, yet so few concrete examples have been substantiated. In this review, we focus on the recent adoption of selected reaction monitoring (SRM) of plasma proteins in the path to clinical use for a broad range of diseases including cancer, cardiovascular disease, genetic disorders and various metabolic disorders. Recent progress reveals a promising outlook for clinical applications using SRM, which now provides the routine analysis of clinically relevant protein markers at low nanogram per millilitre in plasma.     

Mode of drug binding to DNA determined by optical tweezers force spectroscopy

Abstract

Optical tweezers were employed to investigate the effects of small DNA-binding molecules on the low-force (≤ 15 pN) stretching behaviour of single DNA molecules. As the canonical B-DNA helix is not perturbed in this force regime, the effects on DNA elasticity observed upon drug binding provide useful insight into how DNA-binding drugs may alter in vivo processes. In this study, the effects of agents with different DNA binding modes were analysed. DNA force—extension curves were recorded in the presence of netropsin, a purely minor groove-binding antibiotic drug, ethidium bromide, an intercalating fluorescent dye, and berenil, an antiprotozoal drug proposed to exhibit both intercalative and minor groove-binding modes. Applying an approximation of the worm-like chain model, which describes the low-force stretching behaviour, the results were analysed in terms of the DNA contour length and persistence length. From these single molecule studies it was observed that minor groove-binding and intercalating modes of DNA-binding could be distinguished based on changes to DNA elasticity.     

Wool textile identification by terahertz spectroscopy

A variety of woollen textiles were examined using THz time-domain spectroscopy. Textiles containing wool of different animal origins were shown to have different THz optical properties, which may be employed to identify the type of wool and to combat textile counterfeiting.     

Finding unusual medical time-series subsequences: algorithms and applications.

In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of longer time series that are maximally different to all the rest of the time series subsequences. They thus capture the sense of the most unusual subsequence within a time series. While discords have many uses for data mining, they are particularly attractive as anomaly detectors because they only require one intuitive parameter (the length of the subsequence), unlike most anomaly detection algorithms that typically require many parameters. While the brute force algorithm to discover time series discords is quadratic in the length of the time series, we show a simple algorithm that is three to four orders of magnitude faster than brute force, while guaranteed to produce identical results. We evaluate our work with a comprehensive set of experiments on electrocardiograms and other medical datasets.     

Topics in integrated circuits for communications [Series Editorial]

Over the past several years, mobile personal communication devices have converged to a few popular platforms including the smart phone, personal media player, and personal navigation device. More recently, a miniature laptop known as a netbook has also become increasingly widespread. Common in all these devices is the incorporation of multiple communication functions such as personal navigation, personal area networking, local area networking, wireless personal area networking, TV reception, and mobile cellular networking. Moreover, many of these functions are provided via different communications standards; for example, the Global Positioning System (GPS) for personal navigation, IEEE 802.11a/g/n (otherwise known as Wi-Fi) for wireless local area networking, and Bluetooth and IEEE 802.15.4 (ZigBee) for wireless personal area networking. In the case of TV broadcasting, standards are well established but extremely fragmented. A short list of digital TV broadcast standards includes DVB-H, DVB-T, ISDB-T, T-DMB, CMMB, and MediaFLO. Cellular standards likewise are still fragmented based on GSM/EDGE and WCDMA/UMTS although the cellular industry is working diligently toward a consolidated fourth-generation system based on Third Generation Partnership Project (3GPP) Long Term Evolution (LTE).     

Converting non-parametric distance-based classification to anytime algorithms

For many real world problems we must perform classification under widely varying amounts of computational resources. For example, if asked to classify an instance taken from a bursty stream, we may have anywhere from several milliseconds to several minutes to return a class prediction. For such problems an anytime algorithm may be especially useful. In this work we show how we convert the ubiquitous nearest neighbor classifier into an anytime algorithm that can produce an instant classification, or if given the luxury of additional time, can continue computations to increase classification accuracy. We demonstrate the utility of our approach with a comprehensive set of experiments on data from diverse domains. We further show the utility of our work with two deployed applications, in classifying and counting fish, and in classifying insects.