Controllability analysis to identify manipulated variables for a glycosylation control strategy

N-linked glycans affect important end-use characteristics such as the bioactivity and efficacy of many therapeutic proteins, (including monoclonal antibodies), in vivo. However, achieving a precise glycan distribution during manufacturing can be challenging because glycosylation is a non-template driven cellular process, with the potential for significant uncontrolled variability in glycan distributions. As important as the glycan distribution is to the end-use performance of biopharmaceuticals, to date, no strategy exists for controlling glycosylation on-line. In this work, we present a controllability analysis for glycosylation as a first step toward establishing an online glycosylation control strategy. We first assessed the theoretically achievable extent to which the very complex process of glycosylation is controllable. Once theoretic controllability was established, we performed experiments to identify appropriate manipulated variables that can be used to direct the glycan distribution of an IgG1 to a desired state. We found that bioreactor process variables such as glucose and glutamine media concentration, temperature, pH, agitation rate, and dissolved oxygen (DO) had significant but small effects on the relative percentage of various glycans. This indicated that the IgG1 glycan distribution was generally robust to even large perturbations of typical bioreactor variables. Conversely, we found that media supplementation with manganese, galactose, and ammonia had significant and large effects on certain glycans. From this work, we determined that manganese can be used as a manipulated variable to increase the relative abundance of M5 and decrease FA2 glycans simultaneously, and galactose can be used as a manipulated variable to increase the relative abundance of FA2G1 and decrease FA2 and A2 simultaneously. As a final test, we applied machine learning algorithms to validate and enrich these findings from a data-centric point of view. The machine learning algorithms provided an avenue to discover unknown relationships and patterns that refined our findings and provided a framework to explore more variables

Identification of markers linked to genes for sprouting tolerance (independent of grain color) in hard white winter wheat (HWWW)

Key message Hard red wheats can donate genes to hard white wheats for tolerance to preharvest sprouting, the effects are quantitative in nature, and may be tracked with previously described DNA markers. Abstract Pre-harvest sprouting (PHS) of wheat (Triticum aestivum L.) can negatively impact end-use quality and seed viability at planting. Due to preferences for white over red wheat in international markets, white wheat with PHS tolerance has become increasingly desired for worldwide wheat production. In general, however, red wheat is more tolerant of sprouting than white wheat. The main objective of this study was the identification of PHS tolerance conditioned by genes donated from hard red winter wheat, using markers applicable to the Great Plains hard white wheat gene pool. Three red wheat by white wheat populations, Niobrara/NW99L7068, NE98466/NW99L7068 and Jagalene/ NW99L7068 were developed, and white-seeded progenies were analyzed for PHS tolerance and used to identify markers for the trait. In the three populations, marker loci with significant allelic effects were most commonly located on chromosomes of group 2, 3, 4 and 5, though additional markers were detected across the wheat genome. Chromosome 3A was the only chromosome with significant markers in all three populations. Markers were inconsistent across the three populations, and markers linked to tolerance-inducing loci were identified in both tolerant and susceptible parents. Additive effects of marker loci were common. In the present investigation, a wide range of PHS tolerance was observed, even though all lines were fixed for the recently reported positive TaPHS1 allele. PHS tolerance is controlled by additive major gene effects with minor gene effects where variations of minor gene effects were still unclear

Reproducibility, bioinformatic analysis and power of the SAGE method to evaluate changes in transcriptome

The serial analysis of gene expression (SAGE) method is used to study global gene expression in cells or tissues in various experimental conditions. However, its reproducibility has not yet been definitively assessed. In this study, we have evaluated the reproducibility of the SAGE method and identified the factors that affect it. The determination coefficient (R(2)) for the reproducibility of SAGE is 0.96. However, there are some factors that can affect the reproducibility of SAGE, such as the replication of concatemers and ditags, the number of sequenced tags and double PCR amplification of ditags. Thus, corrections for these factors must be made to ensure the reproducibility and accuracy of SAGE results. A bioinformatic analysis of SAGE data is also presented in order to eliminate these artifacts. Finally, the current study shows that increasing the number of sequenced tags improves the power of the method to detect transcripts and their regulation by experimental conditions

How much is enough? Minimal responses of water quality and stream biota to partial retrofit stormwater management in a suburban neighborhood

Decentralized stormwater management approaches (e.g., biofiltration swales, pervious pavement, green roofs, rain gardens) that capture, detain, infiltrate, and filter runoff are now commonly used to minimize the impacts of stormwater runoff from impervious surfaces on aquatic ecosystems. However, there is little research on the effectiveness of retrofit, parcel-scale stormwater management practices for improving downstream aquatic ecosystem health. A reverse auction was used to encourage homeowners to mitigate stormwater on their property within the suburban, 1.8 km2 Shepherd Creek catchment in Cincinnati, Ohio (USA). In 2007–2008, 165 rain barrels and 81 rain gardens were installed on 30% of the properties in four experimental (treatment) subcatchments, and two additional subcatchments were maintained as controls. At the base of the subcatchments, we sampled monthly baseflow water quality, and seasonal (5×/year) physical habitat, periphyton assemblages, and macroinvertebrate assemblages in the streams for the three years before and after treatment implementation. Given the minor reductions in directly connected impervious area from the rain barrel installations (11.6% to 10.4% in the most impaired subcatchment) and high total impervious levels (13.1% to 19.9% in experimental subcatchments), we expected minor or no responses of water quality and biota to stormwater management. There were trends of increased conductivity, iron, and sulfate for control sites, but no such contemporaneous trends for experimental sites. The minor effects of treatment on streamflow volume and water quality did not translate into changes in biotic health, and the few periphyton and macroinvertebrate responses could be explained by factors not associated with the treatment (e.g., vegetation clearing, drought conditions). Improvement of overall stream health is unlikely without additional treatment of major impervious surfaces (including roads, apartment buildings, and parking lots). Further research is needed to define the minimum effect threshold and restoration trajectories for retrofitting catchments to improve the health of stream ecosystems

Genomic diversity in pearl millet inbred lines derived from landraces and improved varieties

Background: Genetic improvement of pearl millet is lagging behind most of the major crops. Development of genomic resources is expected to expedite breeding for improved agronomic traits, stress tolerance, yield, and nutritional quality. Genotyping a breeding population with high throughput markers enables exploration of genetic diversity, population structure, and linkage disequilibrium (LD) which are important preludes for marker-trait association studies and application of genomic-assisted breeding. Results: Genotyping-by-sequencing (GBS) libraries of 309 inbred lines derived from landraces and improved varieties from Africa and India generated 54,770 high quality single nucleotide polymorphism (SNP) markers. On average one SNP per 29 Kb was mapped in the reference genome, with the telomeric regions more densely mapped than the pericentromeric regions of the chromosomes. Population structure analysis using 30,208 SNPs evenly distributed in the genome divided 309 accessions into five subpopulations with different levels of admixture. Pairwise genetic distance (GD) between accessions varied from 0.09 to 0.33 with the average distance of 0.28. Rapid LD decay implied low tendency of markers inherited together. Genetic differentiation estimates were the highest between subgroups 4 and 5, and the lowest between subgroups 1 and 2. Conclusions: Population genomic analysis of pearl millet inbred lines derived from diverse geographic and agroecological features identified five subgroups mostly following pedigree differences with different levels of admixture. It also revealed the prevalence of high genetic diversity in pearl millet, which is very useful in defining heterotic groups for hybrid breeding, trait mapping, and holds promise for improving pearl millet for yield and nutritional quality. The short LD decay observed suggests an absence of persistent haplotype blocks in pearl millet. The diverse genetic background of these lines and their low LD make this set of germplasm useful for traits mapping

A human biomonitoring (HBM) Global Registry Framework: Further advancement of HBM research following the FAIR principles.

Data generated by the rapidly evolving human biomonitoring (HBM) programmes are providing invaluable opportunities to support and advance regulatory risk assessment and management of chemicals in occupational and environmental health domains. However, heterogeneity across studies, in terms of design, terminology, biomarker nomenclature, and data formats, limits our capacity to compare and integrate data sets retrospectively (reuse). Registration of HBM studies is common for clinical trials; however, the study designs and resulting data collections cannot be traced easily. We argue that an HBM Global Registry Framework (HBM GRF) could be the solution to several of challenges hampering the (re)use of HBM (meta)data. The aim is to develop a global, host-independent HBM registry framework based on the use of harmonised open-access protocol templates from designing, undertaking of an HBM study to the use and possible reuse of the resulting HBM (meta)data. This framework should apply FAIR (Findable, Accessible, Interoperable and Reusable) principles as a core data management strategy to enable the (re)use of HBM (meta)data to its full potential through the data value chain. Moreover, we believe that implementation of FAIR principles is a fundamental enabler for digital transformation within environmental health. The HBM GRF would encompass internationally harmonised and agreed open access templates for HBM study protocols, structured web-based functionalities to deposit, find, and access harmonised protocols of HBM studies. Registration of HBM studies using the HBM GRF is anticipated to increase FAIRness of the resulting (meta)data. It is also considered that harmonisation of existing data sets could be performed retrospectively. As a consequence, data wrangling activities to make data ready for analysis will be minimised. In addition, this framework would enable the HBM (inter)national community to trace new HBM studies already in the planning phase and their results once finalised. The HBM GRF could also serve as a platform enhancing communication between scientists, risk assessors, and risk managers/policy makers. The planned European Partnership for the Assessment of Risk from Chemicals (PARC) work along these lines, based on the experience obtained in previous joint European initiatives. Therefore, PARC could very well bring a first demonstration of first essential functionalities within the development of the HBM GRF

Culture-Independent Microbiological Analysis of Foley Urinary Catheter Biofilms

Background: Prevention of catheter-associated urinary tract infection (CAUTI), a leading cause of nosocomial disease, is complicated by the propensity of bacteria to form biofilms on indwelling medical devices [1,2,3,4,5]. Methodology/Principal Findings: To better understand the microbial diversity of these communities, we report the results of a culture-independent bacterial survey of Foley urinary catheters obtained from patients following total prostatectomy. Two patient subsets were analyzed, based on treatment or no treatment with systemic fluoroquinolone antibiotics during convalescence. Results indicate the presence of diverse polymicrobial assemblages that were most commonly observed in patients who did not receive systemic antibiotics. The communities typically contained both Gram-positive and Gramnegative microorganisms that included multiple potential pathogens. Conclusion/Significance: Prevention and treatment of CAUTI must take into consideration the possible polymicrobial nature of any particular infection