Additive and interactive effects of plant genotypic diversity on arthropod communities and plant fitness

Recent research suggests that genetic diversity in plant populations can shape the diversity and abundance of consumer communities. We tested this hypothesis in a field experiment by manipulating patches of Evening Primrose ( Oenothera biennis ) to contain one, four or eight plant genotypes. We then surveyed 92 species of naturally colonizing arthropods. Genetically diverse plant patches had 18% more arthropod species, and a greater abundance of omnivorous and predacious arthropods, but not herbivores, compared with monocultures. The effects of genotypic diversity on arthropod communities were due to a combination of interactive and additive effects among genotypes within genetically diverse patches. Greater genetic diversity also led to a selective feedback, as mean genotype fitness was 27% higher in diverse patches than in monocultures. A comparison between our results and the literature reveals that genetic diversity and species diversity can have similar qualitative and quantitative effects on arthropod communities. Our findings also illustrate the benefit of preserving genetic variation to conserve species diversity and interactions within multitrophic communities.     

Capacity optimization and scheduling of a multiproduct manufacturing facility for biotech products

A general mathematical framework has been proposed in this work for scheduling of a multiproduct and multipurpose facility involving manufacturing of biotech products. The specific problem involves several batch operations occurring in multiple units involving fixed processing time, unlimited storage policy, transition times, shared units, and deterministic and fixed data in the given time horizon. The different batch operations are modeled using state‐task network representation. Two different mathematical formulations are proposed based on discrete‐ and continuous‐time representations leading to a mixed‐integer linear programming model which is solved using General Algebraic Modeling System software. A case study based on a real facility is presented to illustrate the potential and applicability of the proposed models. The continuous‐time model required less number of events and has a smaller problem size compared to the discrete‐time model. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1221–1230, 2014     

Replication arrest is a major threat to growth at low temperature in Antarctic Pseudomonas syringae Lz4W

Chromosomal damage was detected previously in the recBCD mutants of the Antarctic bacterium Pseudomonas syringae Lz4W, which accumulated linear chromosomal DNA leading to cell death and growth inhibition at 4°C. RecBCD protein generally repairs DNA double‐strand breaks by RecA‐dependent homologous recombination pathway. Here we show that ΔrecA mutant of P. syringae is not cold‐sensitive. Significantly, inactivation of additional DNA repair genes ruvAB rescued the cold‐sensitive phenotype of ΔrecBCD mutant. The ΔrecA and ΔruvAB mutants were UV‐sensitive as expected. We propose that, at low temperature DNA replication encounters barriers leading to frequent replication fork (RF) arrest and fork reversal. RuvAB binds to the reversed RFs (RRFs) having Holliday junction‐like structures and resolves them upon association with RuvC nuclease to cause linearization of the chromosome, a threat to cell survival. RecBCD prevents this by degrading the RRFs, and facilitates replication re‐initiation. This model is consistent with our observation that low temperature‐induced DNA lesions do not evoke SOS response in P. syringae. Additional studies show that two other repair genes, radA (encoding a RecA paralogue) and recF are not involved in providing cold resistance to the Antarctic bacterium.     

Activation of Autophagic Flux against Xenoestrogen Bisphenol-A-induced Hippocampal Neurodegeneration via AMP kinase (AMPK)/Mammalian Target of Rapamycin (mTOR) Pathways

The human health hazards related to persisting use of bisphenol-A (BPA) are well documented. BPA-induced neurotoxicity occurs with the generation of oxidative stress, neurodegeneration, and cognitive dysfunctions. However, the cellular and molecular mechanism(s) of the effects of BPA on autophagy and association with oxidative stress and apoptosis are still elusive. We observed that BPA exposure during the early postnatal period enhanced the expression and the levels of autophagy genes/proteins. BPA treatment in the presence of bafilomycin A₁ increased the levels of LC3-II and SQSTM1 and also potentiated GFP-LC3 puncta index in GFP-LC3-transfected hippocampal neural stem cell-derived neurons. BPA-induced generation of reactive oxygen species and apoptosis were mitigated by a pharmacological activator of autophagy (rapamycin). Pharmacological (wortmannin and bafilomycin A₁) and genetic (beclin siRNA) inhibition of autophagy aggravated BPA neurotoxicity. Activation of autophagy against BPA resulted in intracellular energy sensor AMP kinase (AMPK) activation, increased phosphorylation of raptor and acetyl-CoA carboxylase, and decreased phosphorylation of ULK1 (Ser-757), and silencing of AMPK exacerbated BPA neurotoxicity. Conversely, BPA exposure down-regulated the mammalian target of rapamycin (mTOR) pathway by phosphorylation of raptor as a transient cell''s compensatory mechanism to preserve cellular energy pool. Moreover, silencing of mTOR enhanced autophagy, which further alleviated BPA-induced reactive oxygen species generation and apoptosis. BPA-mediated neurotoxicity also resulted in mitochondrial loss, bioenergetic deficits, and increased PARKIN mitochondrial translocation, suggesting enhanced mitophagy. These results suggest implication of autophagy against BPA-mediated neurodegeneration through involvement of AMPK and mTOR pathways. Hence, autophagy, which arbitrates cell survival and demise during stress conditions, requires further assessment to be established as a biomarker of xenoestrogen exposure.     

N type rapid inactivation in human Kv1.4 channels: functional role of a putative C-terminal helix

Voltage gated potassium channels are tetrameric membrane proteins, which have a central role in cellular excitability. Human Kv1.4 channels open on membrane depolarization and inactivate rapidly by a ‘ball and chain’ mechanism whose molecular determinants have been mapped to the cytoplasmic N terminus of the channel. Here we show that the other terminal end of the channel also plays a role in channel inactivation. Swapping the C-terminal residues of hKv1.4 with those from two non-inactivating channels (hKv1.1 and hKv1.2) affects the rates of inactivation, as well as the recovery of the channel from the inactivated state. Secondary structure predictions of the hKv1.4 sequence reveal a helical structure at its distal C-terminal. Complete removal or partial disruption of this helical region results in channels with remarkably slowed inactivation kinetics. The ionic selectivity and voltage-dependence of channel opening were similar to hKv1.4, indicative of an unperturbed channel pore. These results demonstrate that fast inactivation is modulated by structural elements in the C-terminus, suggesting that the process involves the concerted action of the N- and C-termini.     

Using statistical analysis for setting process validation acceptance criteria for biotech products

This paper discusses the challenges of setting process validation acceptance criteria for biotech products for cases where using statistical tools is appropriate. Data are analyzed under three different scenarios that are frequently encountered in biotech applications. Scenario A represents the case when a small data set around center point conditions is available for setting acceptance criteria. Scenario B represents the case when a larger data set within normal operation conditions is available for setting acceptance criteria. Scenario C represents the case when a large characterization data set is available for setting acceptance criteria and it is possible to accurately model the impact of operation conditions on performance of the step. Statistical approaches including mean +/- 3SD, tolerance interval analysis, prediction profiler, and Monte Carlo simulation are applied to the different scenarios. Strengths and shortcomings of the different statistical tools are discussed, and the best approach for each scenario is recommended. It is shown that selection of the right statistical approach is a critical first step toward setting appropriate acceptance criteria.     

Comparison of different options for harvest of a therapeutic protein product from high cell density yeast fermentation broth

Recovery of therapeutic protein from high cell density yeast fermentations at commercial scale is a challenging task. In this study, we investigate and compare three different harvest approaches, namely centrifugation followed by depth filtration, centrifugation followed by filter-aid enhanced depth filtration, and microfiltration. This is achieved by presenting a case study involving recovery of a therapeutic protein from Pichia pastoris fermentation broth. The focus of this study is on performance of the depth filtration and the microfiltration steps. The experimental data has been fitted to the conventional models for cake filtration to evaluate specific cake resistance and cake compressibility. In the case of microfiltration, the experimental data agrees well with flux predicted by shear induced diffusion model. It is shown that, under optimal conditions, all three options can deliver the desired product recovery ( >80%), harvest time ( <15 h including sequential concentration/diafiltration step), and clarification ( <6 NTU). However, the three options differ in terms of process development time required, capital cost, consumable cost, ease of scale-ability and process robustness. It is recommended that these be kept under consideration when making a final decision on a harvesting approach.     

Case study and application of process analytical technology (PAT) towards bioprocessing: Use of tryptophan fluorescence as at‐line tool for making pooling decisions for process chromatography

Process analytical technology (PAT) has been gaining momentum in the biopharmaceutical community due to the potential for continuous real time quality assurance resulting in improved operational control and compliance. Two imperatives for implementing any PAT tool are that “variability is managed by the process” and “product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions.” Recently, we have been examining the feasibility of applying different analytical tools to bioprocessing unit operations. We have previously demonstarted that commercially available online‐high performance liquid chromatography and ultra performance liquid chromatography systems can be used for analysis that can facilitate real‐time decisions for column pooling based on product quality attributes (Rathore et al., 2008 a,b). In this article, we review an at‐line tool that can be used for pooling of process chromatography columns. We have demonstrated that our tryptophan fluorescence method offers a feasible approach and meets the requirements of a PAT application. It is significantly faster than the alternative of fractionation, offline analysis followed by pooling. Although the method as presented here is not an online method, this technique may offer better resolution for certain applications and may be a more optimal approach as it is very conducive to implementation in a manufacturing environment. This technique is also amenable to be used as an online tool via front face fluorescence measurements done concurrently with product concentration determination by UV. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Chemometrics applications in biotech processes: assessing process comparability

A typical biotech process starts with the vial of the cell bank, ends with the final product and has anywhere from 15 to 30 unit operations in series. The total number of process variables (input and output parameters) and other variables (raw materials) can add up to several hundred variables. As the manufacturing process is widely accepted to have significant impact on the quality of the product, the regulatory agencies require an assessment of process comparability across different phases of manufacturing (Phase I vs. Phase II vs. Phase III vs. Commercial) as well as other key activities during product commercialization (process scale-up, technology transfer, and process improvement). However, assessing comparability for a process with such a large number of variables is nontrivial and often companies resort to qualitative comparisons. In this article, we present a quantitative approach for assessing process comparability via use of chemometrics. To our knowledge this is the first time that such an approach has been published for biotech processing. The approach has been applied to an industrial case study involving evaluation of two processes that are being used for commercial manufacturing of a major biosimilar product. It has been demonstrated that the proposed approach is able to successfully identify the unit operations in the two processes that are operating differently. We expect this approach, which can also be applied toward assessing product comparability, to be of great use to both the regulators and the industry which otherwise struggle to assess comparability.