Detecting cell lysis using viscosity monitoring in E. coli fermentation to prevent product loss

Monitoring the physical or chemical properties of cell broths to infer cell status is often challenging due to the complex nature of the broth. Key factors indicative of cell status include cell density, cell viability, product leakage, and DNA release to the fermentation broth. The rapid and accurate prediction of cell status for hosts with intracellular protein products can minimise product loss due to leakage at the onset of cell lysis in fermentation. This article reports the rheological examination of an industrially relevant E. coli fermentation producing antibody fragments (Fab'). Viscosity monitoring showed an increase in viscosity during the exponential phase in relation to the cell density increase, a relatively flat profile in the stationary phase, followed by a rapid increase which correlated well with product loss, DNA release and loss of cell viability. This phenomenon was observed over several fermentations that a 25% increase in broth viscosity (using induction‐point viscosity as a reference) indicated 10% product loss. Our results suggest that viscosity can accurately detect cell lysis and product leakage in postinduction cell cultures, and can identify cell lysis earlier than several other common fermentation monitoring techniques. This work demonstrates the utility of rapidly monitoring the physical properties of fermentation broths, and that viscosity monitoring has the potential to be a tool for process development to determine the optimal harvest time and minimise product loss. © 2016 The Authors. Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers, 32:1069–1076, 2016     

Pollen—Tiny and ephemeral but not forgotten: New ideas on their ecology and evolution

Ecologists and evolutionary biologists have been interested in the functional biology of pollen since the discovery in the 1800s that pollen grains encompass tiny plants (male gametophytes) that develop and produce sperm cells. After the discovery of double fertilization in flowering plants, botanists in the early 1900s were quick to explore the effects of temperature and maternal nutrients on pollen performance, while evolutionary biologists began studying the nature of haploid selection and pollen competition. A series of technical and theoretic developments have subsequently, but usually separately, expanded our knowledge of the nature of pollen performance and how it evolves. Today, there is a tremendous diversity of interests that touch on pollen performance, ranging from the ecological setting on the stigma, structural and physiological aspects of pollen germination and tube growth, the form of pollen competition and its role in sexual selection in plants, virus transmission, mating system evolution, and inbreeding depression. Given the explosion of technical knowledge of pollen cell biology, computer modeling, and new methods to deal with diversity in a phylogenetic context, we are now more than ever poised for a new era of research that includes complex functional traits that limit or enhance the evolution of these deceptively simple organisms.     

A scale‐down mimic for mapping the process performance of centrifugation,depth and sterile filtration

In the production of biopharmaceuticals disk‐stack centrifugation is widely used as a harvest step for the removal of cells and cellular debris. Depth filters followed by sterile filters are often then employed to remove residual solids remaining in the centrate. Process development of centrifugation is usually conducted at pilot‐scale so as to mimic the commercial scale equipment but this method requires large quantities of cell culture and significant levels of effort for successful characterization. A scale‐down approach based upon the use of a shear device and a bench‐top centrifuge has been extended in this work towards a preparative methodology that successfully predicts the performance of the continuous centrifuge and polishing filters. The use of this methodology allows the effects of cell culture conditions and large‐scale centrifugal process parameters on subsequent filtration performance to be assessed at an early stage of process development where material availability is limited. Biotechnol. Bioeng. 2016;113: 1934–1941. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Accounting for the nested nature of genetic variation across levels of organization improves our understanding of biodiversity and community ecology

Recent work has demonstrated that the presence or abundance of specific genotypes, populations, species and phylogenetic clades may influence community and ecosystem properties such as resilience or productivity. Many ecological studies, however, use simple linear models to test for such relationships, including species identity as the predictor variable and some measured trait or function as the response variable without accounting for the nestedness of genetic variation across levels of organization. This omission may lead to incorrect inference about which source of variation influences community and ecosystem properties. Here, we explicitly compare this common approach to alternative ways of modeling variation in trait data, using simulated trait data and empirical results of common‐garden trials using multiple levels of genetic variation within Eucalyptus, Populus and Picea. We show that: 1) when nested variation is ignored, an incorrect conclusion of species effect is drawn in up to 20% of cases; 2) overestimation of the species effect increases – up to 60% in some scenarios – as the nested term explains more of the variation; and 3) the sample sizes needed to overcome these potential problems associated with aggregating nested hierarchical variation may be impractically large. In common‐garden trials, incorporating nested models increased explanatory power twofold for mammal browsing rate in Eucalyptus, threefold for leaf area in Populus, and tenfold for branch number in Picea. Thoroughly measuring intraspecific variation and characterizing hierarchical genetic variation beyond the species level has implications for developing more robust theory in community ecology, managing invaded natural systems, and improving inference in biodiversity–ecosystem functioning research. Synthesis Until recently, ecologists acknowledged the ubiquity of within‐species trait variation, but paid scant attention to how much it affects communities and ecosystems. Here, the authors used simulated trait data and common‐garden studies to demonstrate that we ignore intraspecific trait variation at our peril. In both simulated and experimental systems, in many cases ignoring intraspecific variation led to incorrect statistical inferences and inflated the effect size of species identity. This study shows that ecologists must characterize hierarchically nested genetic and phenotypic variation to fully understand the links between individual traits, community structure and ecosystem functioning.