Accelerating bioprocess development by analysis of all available data: A USP case study

datasets (e.g. time series, quality measurements). By analyzing all available data, bioprocess development can be accelerated. This can only be achieved by having a clearly defined data logging and analysis strategy. Here, we present a case study using available data from the development and optimization of the upstream process (USP) of Sabin inactivated polio vaccine (IPV) using animal component free medium. IPV production using attenuated Sabin strains instead of wild type polio viruses is an initiative supported by the World Health Organization. This change is favorable to reduce the risk of outbreaks during IPV production. Optimizing this process using only animal free components reduces operational costs and lowers the risk of adverse effects related to animal derived compounds. During the process development, 40 bioreactors at scales ranging from 2.3 to 16 L were run. For optimization and robustness studies, design of experiments (DoE) was performed and several USP operational parameters were varied. These included operational mode (batch vs semi-batch), multiplicity of infection (MOI) and time of infection (TOI). This data was routinely analyzed using factors based on DoE methodology. With the new strategy, it became possible to scrutinize all data from the 40 USP development runs in a single data study. The total data package that was analyzed; this included the DoE response parameters, all offline data (e.g. cell, substrate and product concentrations), all data generated by the bioreactor control systems (T, pH, DO, DOCO), and derived calculations (specific rates like µ and qglu). This analysis showed which parameters were most important regarding the bioreactor performance. This USP case study showed that with the new strategy a more detailed, reliable and exact view on the most important parameters regarding bioreactor performance could be obtained. In order to do this, a feature based approach supported by the inCyght® software was utilized. It consisted of logging all data into a database, which was used to determine data integrity for all variables and batches. Exact phase information (cell growth, virus production phase) and other meta information are transferred into the database for each batch. This allowed outliers to be visually determined and certain variables to be excluded from the analysis (i.e. those that did not fluctuate). Univariate outlier detection technique was used to further determine outliers. Principal component analysis (PCA) was used to gain a multivariate process understanding and partial least squares (PLS) regression was performed to identify correlations. This result determined the best subset of variables to be fitted by using multiple linear regression (MLR). Future experiments will focus on the relevant parameters highlighted by this approach. This strategy was applied for the analysis of previously produced data. Further development will use this data analysis methodology for continuous accelerated process development, intensified DoE and integrated process modelling

Single-nucleotide polymorphisms in the Toll-like receptor pathway increase susceptibility to infections in severely injured trauma patients

Background: Sepsis and subsequent multiple-organ failure are the predominant causes of late mortality in trauma patients. Susceptibility and response to infection is, in part, heritable. Single-nucleotide polymorphisms (SNPs) in Toll-like receptor (TLR) and cluster of differentiation 14 (CD14) genes of innate immunity may play a key role. The aim of this study was to assess if SNPs in TLR/CD14 predisposed trauma patients to infection. Methods: A prospective cohort of trauma patients (age 18-80 years; injury severity score [ISS] ≥ 16) admitted to a Level I trauma center between January 2008 and April 2011 was genotyped for SNPs in TLR2 (T-16934A and R753Q), TLR4 (D299G and T399I), TLR9 (T-1486C and T-1237C), and CD14 (C-159T) using high-resolution melting analysis. Association of genotype with prevalence of positive culture findings (gram positive, gram negative, fungi), systemic inflammatory response syndrome (SIRS), sepsis, septic shock, and mortality was tested with χ2and logistic regression analysis. Results: Genotyping was performed for 219 patients, of whom 51% developed positive culture findings in sputum, wounds, blood

Overview of the MOSAiC expedition:Ecosystem

An international and interdisciplinary sea ice drift expedition, the ‘The Multidisciplinary drifting Observatory for the Study of Arctic Climate‘ (MOSAiC), was conducted from October 2019 to September 2020. The aim of MOSAiC was to study the interconnected physical, chemical and biological characteristics and processes from the atmosphere to the deep sea of the central Arctic system. The ecosystem team addressed current knowledge gaps and explored unknown biological properties over a complete seasonal cycle focusing on three major research areas: biodiversity, biogeochemical cycles and linkages to the environment. In addition to the coverage of core properties along a complete seasonal cycle, dedicated projects covered specific processes and habitats, or organisms on higher taxonomic or temporal resolution. A wide range of sampling approaches from sampling, sea ice coring, lead sampling to CTD rosette-based water sampling, plankton nets, ROVs and acoustic buoys was applied to address the science objectives. Further, a wide range of process-related measurements to address e.g. productivity patterns, seasonal migrations and diversity shifts were conducted both in situ and onboard RV Polarstern. This paper provides a detailed overview of the sampling approaches used to address the three main science objectives. It highlights the core sampling program and provides examples of two habitat- or process-specific projects. First results presented include high biological activities in winter time and the discovery of biological hotspots in underexplored habitats. The unique interconnectivity of the coordinated sampling efforts also revealed insights into cross-disciplinary interactions like the impact of biota on Arctic cloud formation. This overview further presents both lessons learned from conducting such a demanding field campaign and an outlook on spin-off projects to be conducted over the next years

Overview of the MOSAiC expedition:Ecosystem

An international and interdisciplinary sea ice drift expedition, the ‘The Multidisciplinary drifting Observatory for the Study of Arctic Climate‘ (MOSAiC), was conducted from October 2019 to September 2020. The aim of MOSAiC was to study the interconnected physical, chemical and biological characteristics and processes from the atmosphere to the deep sea of the central Arctic system. The ecosystem team addressed current knowledge gaps and explored unknown biological properties over a complete seasonal cycle focusing on three major research areas: biodiversity, biogeochemical cycles and linkages to the environment. In addition to the coverage of core properties along a complete seasonal cycle, dedicated projects covered specific processes and habitats, or organisms on higher taxonomic or temporal resolution. A wide range of sampling approaches from sampling, sea ice coring, lead sampling to CTD rosette-based water sampling, plankton nets, ROVs and acoustic buoys was applied to address the science objectives. Further, a wide range of process-related measurements to address e.g. productivity patterns, seasonal migrations and diversity shifts were conducted both in situ and onboard RV Polarstern. This paper provides a detailed overview of the sampling approaches used to address the three main science objectives. It highlights the core sampling program and provides examples of two habitat- or process-specific projects. First results presented include high biological activities in winter time and the discovery of biological hotspots in underexplored habitats. The unique interconnectivity of the coordinated sampling efforts also revealed insights into cross-disciplinary interactions like the impact of biota on Arctic cloud formation. This overview further presents both lessons learned from conducting such a demanding field campaign and an outlook on spin-off projects to be conducted over the next years

Nutrient Availability Controls the Impact of Mammalian Herbivores on Soil Carbon and Nitrogen Pools in Grasslands

Grasslands are subject to considerable alteration due to human activities globally, including widespread changes in populations and composition of large mammalian herbivores and elevated supply of nutrients. Grassland soils remain important reservoirs of carbon (C) and nitrogen (N). Herbivores may affect both C and N pools and these changes likely interact with increases in soil nutrient availability. Given the scale of grassland soil fluxes, such changes can have striking consequences for atmospheric C concentrations and the climate. Here, we use the Nutrient Network experiment to examine the responses of soil C and N pools to mammalian herbivore exclusion across 22 grasslands, under ambient and elevated nutrient availabilities (fertilized with NPK + micronutrients). We show that the impact of herbivore exclusion on soil C and N pools depends on fertilization. Under ambient nutrient conditions, we observed no effect of herbivore exclusion, but under elevated nutrient supply, pools are smaller upon herbivore exclusion. The highest mean soil C and N pools were found in grazed and fertilized plots. The decrease in soil C and N upon herbivore exclusion in combination with fertilization correlated with a decrease in aboveground plant biomass and microbial activity, indicating a reduced storage of organic matter and microbial residues as soil C and N. The response of soil C and N pools to herbivore exclusion was contingent on temperature – herbivores likely cause losses of C and N in colder sites and increases in warmer sites. Additionally, grasslands that contain mammalian herbivores have the potential to sequester more N under increased temperature variability and nutrient enrichment than ungrazed grasslands. Our study highlights the importance of conserving mammalian herbivore populations in grasslands worldwide. We need to incorporate local‐scale herbivory, and its interaction with nutrient enrichment and climate, within global‐scale models to better predict land–atmosphere interactions under future climate change

Crosstalk between androgen receptor and WNT/β-catenin signaling causes sex-specific adrenocortical hyperplasia in mice

Female bias is highly prevalent in conditions such as adrenal cortex hyperplasia and neoplasia, but the reasons behind this phenomenon are poorly understood. In this study, we show that overexpression of the secreted WNT agonist R-spondin 1 (RSPO1) leads to ectopic activation of WNT/β-catenin signaling and causes sex-specific adrenocortical hyperplasia in mice. Although female adrenals show ectopic proliferation, male adrenals display excessive immune system activation and cortical thinning. Using a combination of genetic manipulations and hormonal treatment, we show that gonadal androgens suppress ectopic proliferation in the adrenal cortex and determine the selective regulation of the WNT-related genes Axin2 and Wnt4. Notably, genetic removal of androgen receptor (AR) from adrenocortical cells restores the mitogenic effect of WNT/β-catenin signaling. This is the first demonstration that AR activity in the adrenal cortex determines susceptibility to canonical WNT signaling-induced hyperplasia.</p