The Impact of Retailer-Supplier Cooperation and Decision-Making Uncertainty on Supply Chain Performance

Buyer-supplier relationships have been increasingly considered a critical part of contemporary supply chain management. In response to dynamic and unpredictable market changes, buyers and suppliers enter into cooperative relationships to pursue individual goals and joint goals for better economic and non-economic performance of the supply chain. On the other hand, cooperation between channel members is surrounded by uncertainty, which can create a detrimental impact on the performance of a supply chain. Previous research has focused on various aspects of uncertainty that could affect supply chain member behaviour. The present research contends that relationship behavioural factors play an important role in increasing or mitigating channel members’ perceived uncertainty in their supply or purchase decision-making. Specifically, the purpose of this research is to investigate the impact of retailer-supplier cooperation and retailer/supplier’s decision-making uncertainty (DMU) on retail supply chain performance from the perspectives of both the retailer and the supplier. A holistic model was developed as the theoretical framework for this conceptualisation. A sample of 202 retailers and 64 suppliers in the sporting goods retail business in Taiwan was used to separately test a number of hypothesised relationships by using structural equation modelling (SEM). The findings indicate that both cooperation and DMU are the key determinants of retail supply chain performance, including financial performance and non-financial performance (i.e., supply flexibility and customer service). Financial performance is positively affected by retailer-supplier cooperation and negatively affected by DMU in both the retailer model and the supplier model. The five dimensions of retailer-supplier cooperation (i.e. trust, guanxi, dependence, coercive power and non-coercive power) have significant effects on cooperation. However, apart from guanxi with the retailer/supplier, neither other relationship dimensions nor retailer-supplier cooperation have any influence on retailer’s DMU or supplier’s DMU. The results also indicate that differences and similarities exist across retailers and suppliers with respect to the effects of several relationship dimensions on cooperation and uncertainty. 2 The holistic empirical model developed for this research contributes further to understanding the links, which have been lacking in the extant channel relationship literature and supply chain management literature, between buyer-supplier relationships, DMU, and supply chain performance. The findings that a retailer/supplier’s DMU can erode the performance of a supply chain in various aspects highlight the need for improvement in some areas of supply chain efficiency and effectiveness, through cooperation-enhancing actions between the retailer and the supplier. From a managerial perspective, the performance improvement in the supply chain, in turn, will motivate more reciprocal commitment and efforts from the retailer and the supplier to maintain their working relationship. As such, mutual trust and enriched guanxi, dependence and non-coercive power help both the retailer and the supplier to have less uncertainty in their purchase/supply decision-making process. It creates a win-win position for both parties in the supply chain

Capturing the facets of evolvability in a mechanistic framework

‘Evolvability’ – the ability to undergo adaptive evolution – is a key concept for understanding and predicting the response of biological systems to environmental change. Evolvability has various facets and is applied in many ways, easily leading to misunderstandings among researchers. To clarify matters, we first categorize the mechanisms and organismal features underlying evolvability into determinants providing variation, determinants shaping the effect of variation on fitness, and determinants shaping the selection process. Second, we stress the importance of timescale when studying evolvability. Third, we distinguish between evolvability determinants with a broad and a narrow scope. Finally, we highlight two contrasting perspectives on evolvability: general evolvability and specific evolvability. We hope that this framework facilitates communication and guides future research

Natural supramolecular protein assemblies

Supramolecular protein assemblies are an emerging area within the chemical sciences, which combine the topological structures of the field of supramolecular chemistry and the state-of-the-art chemical biology approaches to unravel the formation and function of protein assemblies. Recent chemical and biological studies on natural multimeric protein structures, including fibers, rings, tubes, catenanes, knots, and cages, have shown that the quaternary structures of proteins are a prerequisite for their highly specific biological functions. In this review, we illustrate that a striking structural diversity of protein assemblies is present in nature. Furthermore, we describe structure–function relationship studies for selected classes of protein architectures, and we highlight the techniques that enable the characterisation of supramolecular protein structures

Selective Proteomic Analysis of Antibiotic-Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms

Biofilm infections exhibit high tolerance against antibiotic treatment. The study of biofilms is complicated by phenotypic heterogeneity; biofilm subpopulations differ in their metabolic activities and their responses to antibiotics. Here, we describe the use of the bio-orthogonal noncanonical amino acid tagging (BONCAT) method to enable selective proteomic analysis of a Pseudomonas aeruginosa biofilm subpopulation. Through controlled expression of a mutant methionyl-tRNA synthetase, we targeted BONCAT labeling to cells in the regions of biofilm microcolonies that showed increased tolerance to antibiotics. We enriched and identified proteins synthesized by cells in these regions. Compared to the entire biofilm proteome, the labeled subpopulation was characterized by a lower abundance of ribosomal proteins and was enriched in proteins of unknown function. We performed a pulse-labeling experiment to determine the dynamic proteomic response of the tolerant subpopulation to supra-MIC treatment with the fluoroquinolone antibiotic ciprofloxacin. The adaptive response included the upregulation of proteins required for sensing and repairing DNA damage and substantial changes in the expression of enzymes involved in central carbon metabolism. We differentiated the immediate proteomic response, characterized by an increase in flagellar motility, from the long-term adaptive strategy, which included the upregulation of purine synthesis. This targeted, selective analysis of a bacterial subpopulation demonstrates how the study of proteome dynamics can enhance our understanding of biofilm heterogeneity and antibiotic tolerance.IMPORTANCE Bacterial growth is frequently characterized by behavioral heterogeneity at the single-cell level. Heterogeneity is especially evident in the physiology of biofilms, in which distinct cellular subpopulations can respond differently to stresses, including subpopulations of pathogenic biofilms that are more tolerant to antibiotics. Global proteomic analysis affords insights into cellular physiology but cannot identify proteins expressed in a particular subpopulation of interest. Here, we report a chemical biology method to selectively label, enrich, and identify proteins expressed by cells within distinct regions of biofilm microcolonies. We used this approach to study changes in protein synthesis by the subpopulation of antibiotic-tolerant cells throughout a course of treatment. We found substantial differences between the initial response and the long-term adaptive strategy that biofilm cells use to cope with antibiotic stress. The method we describe is readily applicable to investigations of bacterial heterogeneity in diverse contexts

Selective proteomic analysis of antibiotic-tolerant cellular subpopulations in pseudomonas aeruginosa biofilms

Biofilm infections exhibit high tolerance against antibiotic treatment. The study of biofilms is complicated by phenotypic heterogeneity; biofilm subpopulations differ in their metabolic activities and their responses to antibiotics. Here, we describe the use of the bio-orthogonal noncanonical amino acid tagging (BONCAT) method to enable selective proteomic analysis of a Pseudomonas aeruginosa biofilm subpopulation. Through controlled expression of a mutant methionyl-tRNA synthetase, we targeted BONCAT labeling to cells in the regions of biofilm microcolonies that showed increased tolerance to antibiotics. We enriched and identified proteins synthesized by cells in these regions. Compared to the entire biofilm proteome, the labeled subpopulation was characterized by a lower abundance of ribosomal proteins and was enriched in proteins of unknown function. We performed a pulse-labeling experiment to determine the dynamic proteomic response of the tolerant subpopulation to supra-MIC treatment with the fluoroquinolone antibiotic ciprofloxacin. The adaptive response included the upregulation of proteins required for sensing and repairing DNA damage and substantial changes in the expression of enzymes involved in central carbon metabolism. We differentiated the immediate proteomic response, characterized by an increase in flagellar motility, from the long-term adaptive strategy, which included the upregulation of purine synthesis. This targeted, selective analysis of a bacterial subpopulation demonstrates how the study of proteome dynamics can enhance our understanding of biofilm heterogeneity and antibiotic tolerance

Temperature-Induced Collapse of Elastin-like Peptides Studied by 2DIR Spectroscopy

Elastin-like peptides are hydrophobic biopolymers that exhibit a reversible coacervation transition when the temperature is raised above a critical point. Here, we use a combination of linear infrared spectroscopy, two-dimensional infrared spectroscopy, and molecular dynamics simulations to study the structural dynamics of two elastin-like peptides. Specifically, we investigate the effect of the solvent environment and temperature on the structural dynamics of a short (5-residue) elastin-like peptide and of a long (450-residue) elastin-like peptide. We identify two vibrational energy transfer processes that take place within the amide I' band of both peptides. We observe that the rate constant of one of the exchange processes is strongly dependent on the solvent environment and argue that the coacervation transition is accompanied by a desolvation of the peptide backbone where up to 75% of the water molecules are displaced. We also study the spectral diffusion dynamics of the valine(1) residue that is present in both peptides. We find that these dynamics are relatively slow and indicative of an amide group that is shielded from the solvent. We conclude that the coacervation transition of elastin-like peptides is probably not associated with a conformational change involving this residue

Selective Proteomic Analysis of Antibiotic-Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms

Biofilm infections exhibit high tolerance against antibiotic treatment. The study of biofilms is complicated by phenotypic heterogeneity; biofilm subpopulations differ in their metabolic activities and their responses to antibiotics. Here, we describe the use of the bio-orthogonal noncanonical amino acid tagging (BONCAT) method to enable selective proteomic analysis of a Pseudomonas aeruginosa biofilm subpopulation. Through controlled expression of a mutant methionyl-tRNA synthetase, we targeted BONCAT labeling to cells in the regions of biofilm microcolonies that showed increased tolerance to antibiotics. We enriched and identified proteins synthesized by cells in these regions. Compared to the entire biofilm proteome, the labeled subpopulation was characterized by a lower abundance of ribosomal proteins and was enriched in proteins of unknown function. We performed a pulse-labeling experiment to determine the dynamic proteomic response of the tolerant subpopulation to supra-MIC treatment with the fluoroquinolone antibiotic ciprofloxacin. The adaptive response included the upregulation of proteins required for sensing and repairing DNA damage and substantial changes in the expression of enzymes involved in central carbon metabolism. We differentiated the immediate proteomic response, characterized by an increase in flagellar motility, from the long-term adaptive strategy, which included the upregulation of purine synthesis. This targeted, selective analysis of a bacterial subpopulation demonstrates how the study of proteome dynamics can enhance our understanding of biofilm heterogeneity and antibiotic tolerance.IMPORTANCE Bacterial growth is frequently characterized by behavioral heterogeneity at the single-cell level. Heterogeneity is especially evident in the physiology of biofilms, in which distinct cellular subpopulations can respond differently to stresses, including subpopulations of pathogenic biofilms that are more tolerant to antibiotics. Global proteomic analysis affords insights into cellular physiology but cannot identify proteins expressed in a particular subpopulation of interest. Here, we report a chemical biology method to selectively label, enrich, and identify proteins expressed by cells within distinct regions of biofilm microcolonies. We used this approach to study changes in protein synthesis by the subpopulation of antibiotic-tolerant cells throughout a course of treatment. We found substantial differences between the initial response and the long-term adaptive strategy that biofilm cells use to cope with antibiotic stress. The method we describe is readily applicable to investigations of bacterial heterogeneity in diverse contexts

Evolvability in the context of antibiotic resistance

The rise of antibiotic resistance is an example of ‘evolution in action’: bacterial populations adapt to a toxic environment by evolving resistance. However, luckily, bacterial populations are not always able to adapt to survive antibiotic exposure. What determines if a bacterial population will develop resistance? To answer this question, we need to understand the mechanisms that enable bacterial populations to undergo adaptive evolution. In other words, we need to understand ‘evolvability’ in the context of antibiotic resistance. In this PhD thesis, I use a combined theoretical and experimental approach to investigate three mechanisms that underlie bacterial evolvability: mutation rates, gene regulatory network architecture, and horizontal gene transfer. Regarding mutation rates, I show that evolution tailors these to the local conditions. Under stressful conditions, mutation rates should increase, thus enhancing bacterial evolvability. Experimentally, I demonstrate that the mutation rate towards antibiotic resistance is indeed impacted by environmental temperature, a finding of potential clinical relevance. Regarding gene regulation, I show using a model that the architecture of a gene regulatory network tends to evolve in such a way that the phenotypic effects of genetically random mutations are biased towards adaptive outcomes, which facilitates rapid adaptation. Regarding horizontal gene transfer, I examined the role that plasmids play in the emergence of antibiotic resistance using experimental evolution. Contrary to expectations, I showed that in the context of my experiment plasmids do not enhance the rate of resistance evolution. The thesis closes with a discussion of the clinical relevance of the insights obtained