Explore the vast range of titles available.

Recent advancements in mRNA technology, utilized in vaccines, immunotherapies, protein replacement therapies, and genome editing, have emerged as promising and increasingly viable treatments. The rapid, potent, and transient properties of mRNA-encoded proteins make them attractive tools for the effective treatment of a variety of conditions, ranging from infectious diseases to cancer and single-gene disorders. The capability for rapid and large-scale production of mRNA therapeutics fueled the global response to the COVID-19 pandemic. For effective clinical implementation, it is crucial to deeply characterize and control important mRNA attributes such as purity/integrity, identity, structural quality features, and functionality. This implies the use of powerful and advanced analytical techniques for quality control and characterization of mRNA. Improvements in analytical techniques such as electrophoresis, chromatography, mass spectrometry, sequencing, and functionality assessments have significantly enhanced the quality and detail of information available for product and process characterization, as well as for routine stability and release testing. Here, we review the latest advancements in analytical techniques for the characterization of mRNA-based therapeutics, typically employed by the biopharmaceutical industry for eventual market release.

The antibody- FcγRIIIa interaction triggers key immunological responses such as antibody dependent cellular cytotoxicity (ADCC), making it highly important for therapeutic mAbs. Due to the direct glycan-glycan interaction with FcγRIIIa receptor, differences in antibody glycosylation can drastically influence the binding affinity. Understanding the differential binding of mAb glycoforms is a very important, yet challenging task due to the co-existence of multiple glycoforms in a sample. Affinity liquid chromatography (AC) and affinity capillary electrophoresis (ACE) hyphenated with mass spectrometry (MS) can provide glycoform-resolved affinity profiles of proteins based on their differences in either dissociation (AC) or equilibrium (ACE) constants. To cross-validate the affinity ranking provided by these complementary novel approaches, both techniques were benchmarked using the same FcγRIIIa constructs. Both approaches were able to assess the mAb – FcγRIIIa interaction in a glycoform selective manner and showed a clear increase in binding for fully versus hemi-fucosylated mAbs. Also, other features, such as increasing affinity with elevated galactosylation or the binding affinity for high mannose glycoforms were consistent. We further applied these approaches to assess the binding towards the F158 allotype of FcγRIIIa, which was not reported before. The FcγRIIIa F158 allotype showed a very similar profile compared to the V158 receptor with the strongest increase in binding due to afucosylation and only a slight increase in binding with additional galactosylation. Both techniques showed a decrease of the binding affinity for high mannose glycoforms for FcγRIIIa F158 compared to the V158 variant. Overall, both approaches provided very comparable results in line with orthogonal methods proving the capabilities of separation-based affinity approaches to study FcγR binding of antibody glycoforms.

Human Fc gamma receptor IIa (FcγRIIa) or CD32a has two major allotypes with a single amino acid difference at position 131 (histidine or arginine). Differences in FcγRIIa allotypes are known to impact immunological responses such as the clinical outcome of therapeutic monoclonal antibodies (mAbs). FcγRIIa is involved in antibody-dependent cellular phagocytosis (ADCP), which is an important contributor to the mechanism-of-action of mAbs by driving phagocytic clearance of cancer cells. Hence, understanding the impact of individual mAb proteoforms on the binding to FcγRIIa, and its different allotypes, is crucial for defining meaningful critical quality attributes (CQAs). Here, we report a function-structure based approach guided by novel FcγRIIa affinity chromatography-mass spectrometry (AC-MS) assays to assess individual IgG1 proteoforms. This allowed to unravel allotype-specific differences of IgG1 proteoforms on FcγRIIa binding. FcγRIIa AC-MS confirmed and refined structure-function relationships of IgG1 glycoform interactions. For example, the positive impact of afucosylation was higher than galactosylation for FcγRIIa Arg compared to FcγRIIa His. Moreover, we observed FcγRIIa allotype-opposing and IgG1 proteoform integrity-dependent differences in the binding response of stress-induced IgG1 proteoforms comprising asparagine 325 deamidation. The FcγRIIa-allotype dependent binding differences resolved by AC-MS were in line with functional ADCP-surrogate bioassay models. The molecular basis of the observed allotype specificity and proteoform selectivity upon asparagine 325 deamidation was elucidated using molecular dynamics. The observed differences were attributed to the contributions of an inter-molecular salt bridge between IgG1 and FcγRIIa Arg and the contribution of an intra-molecular hydrophobic pocket in IgG1. Our work highlights the unprecedented structural and functional resolution of AC-MS approaches along with predictive biological significance of observed affinity differences within relevant cell-based methods. This makes FcγRIIa AC-MS an invaluable tool to streamline the CQA assessment of therapeutic mAbs.

Glycoproteomic data are often very complex, reflecting the high structural diversity of peptide and glycan portions. The use of glycopeptide-centered glycoproteomics by mass spectrometry is rapidly evolving in many research areas, leading to a demand in reliable data analysis tools. In recent years, several bioinformatic tools were developed to facilitate and improve both the identification and quantification of glycopeptides. Here, a selection of these tools was combined and evaluated with the aim of establishing a robust glycopeptide detection and quantification workflow targeting enriched glycoproteins. For this purpose, a tryptic digest from affinity-purified immunoglobulins G and A was analyzed on a nano-reversed-phase liquid chromatography–tandem mass spectrometry platform with a high-resolution mass analyzer and higher-energy collisional dissociation fragmentation. Initial glycopeptide identification based on MS/MS data was aided by the Byonic software. Additional MS1-based glycopeptide identification relying on accurate mass and retention time differences using GlycopeptideGraphMS considerably expanded the set of confidently annotated glycopeptides. For glycopeptide quantification, the performance of LaCyTools was compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the automated processing of several IgA glycopeptides. Finally, this study presents a semiautomated workflow for reliable glycoproteomic data analysis by the combination of software packages for MS/MS- and MS1-based glycopeptide identification as well as the integration of analyte quality control and quantification.

We present results of the first large-scale interlaboratory study carried out in synthetic biology, as part of the 2014 and 2015 International Genetically Engineered Machine (iGEM) competitions. Participants at 88 institutions around the world measured fluorescence from three engineered constitutive constructs in E. coli. Few participants were able to measure absolute fluorescence, so data was analyzed in terms of ratios. Precision was strongly related to fluorescent strength, ranging from 1.54-fold standard deviation for the ratio between strong promoters to 5.75-fold for the ratio between the strongest and weakest promoter, and while host strain did not affect expression ratios, choice of instrument did. This result shows that high quantitative precision and reproducibility of results is possible, while at the same time indicating areas needing improved laboratory practices.

Background X-ray computed tomography is acknowledged as a powerful tool for the study of root system architecture of plants growing in soil. In this paper, we improved the original root segmentation algorithm “Rootine” and present its succeeding version “Rootine v.2”. In addition to gray value information, Rootine algorithms are based on shape detection of cylindrical roots. Both algorithms are macros for the ImageJ software and are made freely available to the public. New features in Rootine v.2 are (i) a pot wall detection and removal step to avoid segmentation artefacts for roots growing along the pot wall, (ii) a calculation of the root average gray value based on a histogram analysis, (iii) an automatic calculation of thresholds for hysteresis thresholding of the tubeness image to reduce the number of parameters and (iv) a false negatives recovery based on shape criteria to increase root recovery. We compare the segmentation results of Rootine v.1 and Rootine v.2 with the results of root washing and subsequent analysis with WinRhizo. We use a benchmark dataset of maize roots ( Zea mays L. cv. B73) grown in repacked soil for two scenarios with differing soil heterogeneity and image quality. Results We demonstrate that Rootine v.2 outperforms its preceding version in terms of root recovery and enables to match better the root diameter distribution data obtained with root washing. Despite a longer processing time, Rootine v.2 comprises less user-defined parameters and shows an overall greater usability. Conclusion The proposed method facilitates higher root detection accuracy than its predecessor and has the potential for improving high-throughput root phenotyping procedures based on X-ray computed tomography data analysis.

Aims Root hairs are one root trait among many which enables plants to adapt to environmental conditions. How different traits are coordinated and whether some are mutually exclusive is currently poorly understood. Comparing a root hair defective mutant with its corresponding wild-type, we explored if and how the mutant exhibited root growth adaptation strategies and how dependent this was on substrate. Methods Zea mays root hair defective mutant ( rth3 ) and the corresponding wild-type siblings were grown under well-watered conditions on two substrates with contrasting texture and hence nutrient mobility. Root system architecture was investigated over time using repeated X-ray computed tomography. Results There was no plastic adaptation of root system architecture to the lack of root hairs, which resulted in lower uptake of nutrients especially in the substrate with high sorption capacity. The function of the root hairs for anchoring did not result in different root length density profiles between genotypes. Both maize genotypes showed a marked response to substrate. This was well reflected in the spatiotemporal development of rhizosphere volume fraction but especially in the highly significant response of root diameter to substrate, irrespective of genotype. Conclusions The most salient root plasticity trait was root diameter in response to substrate. Coping mechanisms for missing root hairs were limited to a shift in root-shoot ratio in loam. Further experiments are required, to elucidate whether observed differences can be explained by mechanical properties beyond mechanical impedance, root or microbiome ethylene production or differences in diffusion processes within the root or the rhizosphere.

Aims Root hairs and lateral growth are root traits among many which enable plants to adapt to environmental conditions. How different traits are coordinated under local heterogeneity, especially when two or more environmental factors vary in space, is currently poorly understood. We investigated the effect of heterogeneity on root system architecture of maize in response to the presence of loamy macroaggregates, which come along with both, increased penetration resistance and nutrient availability, i.e., two important environmental factors shaping root system architecture. The comparison between a mutant with defective root hairs and the corresponding wild type made it possible to investigate the importance of root hairs in the adaptation strategies of plant roots to these factors. Methods Changes in root growth and root distribution with respect to macroaggregates were investigated using X-ray computed tomography. The wild-type of Zea mays L. was compared with the root hair defective mutant ( rth3 ) to investigate the importance of root hairs in addition to adaption of root architecture. Results The presence of aggregates lead to increased root length and branch densities around aggregates, while only a few roots were able to grow into them. Thereby, wildtype and rth3 were influenced in the same way. Aboveground biomass, however, was not affected by the presence of macroaggregates, as compared to controls with homogenously distributed loam. Conclusions Macroaggregation of loam in sandy soil shows little influence on maize growth, due to local adaptations of root architecture to the heterogeneity in nutrient availability and penetration resistance caused by the aggregates.

Aims Root hairs are important for uptake, especially for nutrients with low mobility in soils with high sorption capacity. Mutants with defective root hairs are expected to have lower nutrient uptake, unless they compensate with more root growth. Since root hairs can also contribute to the plant's water uptake their importance could change over the course of a growing season. It was our objective to investigate the role of root hairs under field conditions. Methods The root hair mutant rth3 of Zea mays and the corresponding wild-type were grown for two years under field conditions on sand and loam. Results Shoot growth and P and K uptake of the plants were promoted by the presence of hairs at all growth stages. Differences between genotypes were greater on loam than on sand until tassel emergence, presumably as additional exploitation by hairs is more relevant in loam. Compensation for the absence of root hairs by increased root growth was not observed in absolute terms. The root to shoot ratio was higher for rth3 than for wild-type. Root traits showed high plasticity in response to texture, the most salient being a greater mean root diameter in sand, irrespective of genotype. The mechanism causing the increase in mean root diameter is still unknown. Root length density was higher in sand, which can be explained by a greater need for exploration than exploitation in this substrate. Conclusion The role of hairs for nutrient uptake could be confirmed under field conditions. The large impact of texture on root growth and consequences for carbon balance require further investigations.

Roots are highly plastic organs enabling plants to acclimate to a changing below-ground environment. In addition to abiotic factors like nutrients or mechanical resistance, plant roots also respond to temperature variation. Below the heat stress threshold, Arabidopsis thaliana seedlings react to elevated temperature by promoting primary root growth, possibly to reach deeper soil regions with potentially better water saturation. While above-ground thermomorphogenesis is enabled by thermo-sensitive cell elongation, it was unknown how temperature modulates root growth. We here show that roots are able to sense and respond to elevated temperature independent of shoot-derived signals. An unknown root thermosensor seems to employ auxin as a messenger to promote primary root growth. Growth is primarily achieved by accelerating cell division rates in the root apical meristem, likely maintained via temperature-sensitive organization of the polar auxin transport system. Hence, the primary cellular target of elevated ambient temperature differs fundamentally between root and shoot tissues, while the messenger auxin that relays temperature information to elongating or dividing cells, respectively, remains the same.