Cross-scale quality assessment of a mechanistic cation exchange chromatography model

Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing-scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing-scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass-action (SMA) adsorption model was applied to the scale-up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory- to manufacturing-scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large-scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches.     

Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe

Recent studies from mountainous areas of small spatial extent (<2500 km²) suggest that fine‐grained thermal variability over tens or hundreds of metres exceeds much of the climate warming expected for the coming decades. Such variability in temperature provides buffering to mitigate climate‐change impacts. Is this local spatial buffering restricted to topographically complex terrains? To answer this, we here study fine‐grained thermal variability across a 2500‐km wide latitudinal gradient in Northern Europe encompassing a large array of topographic complexities. We first combined plant community data, Ellenberg temperature indicator values, locally measured temperatures (LmT) and globally interpolated temperatures (GiT) in a modelling framework to infer biologically relevant temperature conditions from plant assemblages within <1000‐m² units (community‐inferred temperatures: CiT). We then assessed: (1) CiT range (thermal variability) within 1‐km² units; (2) the relationship between CiT range and topographically and geographically derived predictors at 1‐km resolution; and (3) whether spatial turnover in CiT is greater than spatial turnover in GiT within 100‐km² units. Ellenberg temperature indicator values in combination with plant assemblages explained 46–72% of variation in LmT and 92–96% of variation in GiT during the growing season (June, July, August). Growing‐season CiT range within 1‐km² units peaked at 60–65°N and increased with terrain roughness, averaging 1.97 °C (SD = 0.84 °C) and 2.68 °C (SD = 1.26 °C) within the flattest and roughest units respectively. Complex interactions between topography‐related variables and latitude explained 35% of variation in growing‐season CiT range when accounting for sampling effort and residual spatial autocorrelation. Spatial turnover in growing‐season CiT within 100‐km² units was, on average, 1.8 times greater (0.32 °C km^?1) than spatial turnover in growing‐season GiT (0.18 °C km^?1). We conclude that thermal variability within 1‐km² units strongly increases local spatial buffering of future climate warming across Northern Europe, even in the flattest terrains.     

Environmental gradients shift the direction of the relationship between native and alien plant species richness

Aim

To assess how environmental, biotic and anthropogenic factors shape native–alien plant species richness relationships across a heterogeneous landscape.

Location

Banks Peninsula, New Zealand.

Methods

We integrated a comprehensive floristic survey of over 1200 systematically located 6 × 6 m plots, with corresponding climate, environmental and anthropogenic data. General linear models examined variation in native and alien plant species richness across the entire landscape, between native‐ and alien‐dominated plots, and within separate elevational bands.

Results

Across all plots, there was a significant negative correlation between native and alien species richness, but this relationship differed within subsets of the data: the correlation was positive in alien‐dominated plots but negative in native‐dominated plots. Within separate elevational bands, native and alien species richness were positively correlated at lower elevations, but negatively correlated at higher elevations. Alien species richness tended to be high across the elevation gradient but peaked in warmer, mid‐ to low‐elevation sites, while native species richness increased linearly with elevation. The negative relationship between native and alien species richness in native‐dominated communities reflected a land‐use gradient with low native and high alien richness in more heavily modified native‐dominated vegetation. In contrast, native and alien richness were positively correlated in very heavily modified alien‐dominated plots, most likely due to covariation along a gradient of management intensity.

Main conclusions

Both positive and negative native–alien richness relationships can occur across the same landscape, depending on the plant community and the underlying human and environmental gradients examined. Human habitat modification, which is often confounded with environmental variation, can result in high alien and low native species richness in areas still dominated by native species. In the most heavily human modified areas, dominated by alien species, both native and alien species may be responding to similar underlying gradients.

     

Integrating frugivory and animal movement: a review of the evidence and implications for scaling seed dispersal

General principles about the consequences of seed dispersal by animals for the structure and dynamics of plant populations and communities remain elusive. This is in part because seed deposition patterns emerge from interactions between frugivore behaviour and the distribution of food resources, both of which can vary over space and time. Here we advocate a frugivore‐centred, process‐based, synthetic approach to seed dispersal research that integrates seed dispersal ecology and animal movement across multiple spatio‐temporal scales. To guide this synthesis, we survey existing literature using paradigms from seed dispersal and animal movement. Specifically, studies are discussed with respect to five criteria: selection of focal organisms (animal or plant); measurement of animal movement; characterization of seed shadow; animal, plant and environmental factors included in the study; and scales of the study. Most studies focused on either frugivores or plants and characterized seed shadows directly by combining gut retention time with animal movement data or indirectly by conducting maternity analysis of seeds. Although organismal traits and environmental factors were often measured, they were seldom used to characterize seed shadows. Multi‐scale analyses were rare, with seed shadows mostly characterized at fine spatial scales, over single fruiting seasons, and for individual dispersers. Novel animal‐ and seed‐tracking technologies, remote environmental monitoring tools, and advances in analytical methods can enable effective implementation of a hierarchical mechanistic approach to the study of seed dispersal. This kind of mechanistic approach will provide novel insights regarding the complex interplay between the factors that modulate animal behaviour and subsequently influence seed dispersal patterns across spatial and temporal scales.     

Biogeography of the ecosystems of the healthy human body

Background

Characterizing the biogeography of the microbiome of healthy humans is essential for understanding microbial associated diseases. Previous studies mainly focused on a single body habitat from a limited set of subjects. Here, we analyzed one of the largest microbiome datasets to date and generated a biogeographical map that annotates the biodiversity, spatial relationships, and temporal stability of 22 habitats from 279 healthy humans.

Results

We identified 929 genera from more than 24 million 16S rRNA gene sequences of 22 habitats, and we provide a baseline of inter-subject variation for healthy adults. The oral habitat has the most stable microbiota with the highest alpha diversity, while the skin and vaginal microbiota are less stable and show lower alpha diversity. The level of biodiversity in one habitat is independent of the biodiversity of other habitats in the same individual. The abundances of a given genus at a body site in which it dominates do not correlate with the abundances at body sites where it is not dominant. Additionally, we observed the human microbiota exhibit both cosmopolitan and endemic features. Finally, comparing datasets of different projects revealed a project-based clustering pattern, emphasizing the significance of standardization of metagenomic studies.

Conclusions

The data presented here extend the definition of the human microbiome by providing a more complete and accurate picture of human microbiome biogeography, addressing questions best answered by a large dataset of subjects and body sites that are deeply sampled by sequencing.     

Insights into ALS pathomechanisms: from flies to humans

Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease causing the death of motor neurons with consequent muscle atrophy and paralysis. Several neurodegenerative diseases have been modeled in Drosophila and genetic studies on this model organism led to the elucidation of crucial aspects of disease mechanisms. ALS, however, has lagged somewhat behind possibly because of the lack of a suitable genetic model. We were the first to develop a fly model for ALS and over the last few years, we have implemented and used this model for a large scale, unbiased modifier screen. We also report an extensive bioinformatic analysis of the genetic modifiers and we show that most of them are associated in a network of interacting genes controlling known as well as novel cellular processes involved in ALS pathogenesis. A similar analysis for the human homologues of the Drosophila modifiers and the validation of a subset of them in human tissues confirm and expand the significance of the data for the human disease. Finally, we analyze a possible application of the model in the process of therapeutic discovery in ALS and we discuss the importance of novel “non-obvious” models for the disease.     

Are Sage-Grouse Fine-Scale Specialists or Shrub-Steppe Generalists?

Sage-grouse (Centrocercus spp.) are influencing rapidly evolving land management policy in the western United States. Management objectives for fine-scale vegetation characteristics (e.g., grass height >18 cm) have been adopted by land management agencies based on resource selection or relationships with fitness proxies reported among numerous habitat studies. Some managers, however, have questioned the appropriateness of these objectives. Moreover, it remains untested whether habitat–fitness relationships documented at fine scales (i.e., among individual nests within a study area) also apply at scales of management units (e.g., pastures or grazing allotments), which are many orders of magnitude larger. We employed meta-analyses of studies published from 1991 to 2019 to help resolve the role of fine-scale vegetation structure in nest site selection and nest success across the geographic range of greater sage-grouse (C. urophasianus) and evaluate the validity of established habitat management objectives. Specifically, we incorporated effects of study design and functional responses to resource availability in meta-regression models linking vegetation structure to nest site selection, and used a novel meta-analytic approach to simultaneously model vegetation structure and its relationship to nest success. Our approach tested habitat relationships at a range-wide extent and a grain size closely matching scales at which agencies make management decisions. We found moderate, but context-dependent, effects of shrub characteristics and weak effects of herbaceous vegetation on nest site selection. None of the tested vegetation characteristics were related to variation in nest success, suggesting nesting habitat–fitness relationships have been inappropriately extrapolated in developing range-wide habitat management objectives. Our findings reveal surprising flexibility in habitat use for a species often depicted as having very particular fine-scale habitat requirements, and cast doubt on the practice of adopting precise management objectives for vegetation structure based on findings of individual small-scale field studies. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

Leveraging flow mechanics to determine critical process and scaling parameters in a continuous viral inactivation reactor

A continuous viral inactivation (CVI) chamber has been designed to operate with acceptable residence time distribution (RTD) characteristics. However, altering the CVI's geometry and operation to accommodate the scale was not obvious. In this work, we elucidate the influence of Dean vortices and leverage the transition into the weak turbulent regime to establish relationships between input variables and process outputs. This study was targeted to understand and quantify the impact of viscosity, Dean number, internal diameter, and path length on the RTD. When the Dean number exceeds 70, radial mixing generated by the Dean vortices began to consistently alter the axial dispersive effects experienced by the pulse injection. Increasing to a Dean number of >100, the axial dispersive effects were dominated by the Dean vortices which allowed the calculation of the minimum and maximum residence time to be generated. This work provides a method to calculate operational solutions for a tubular incubation reactor in terms of path length, internal diameter, flow rate, and target minimum and maximum residence time specifications that assures both viral residence times while also establishing criteria to maximize product quality during continuous operation.