Combination Effects of Antimicrobial Peptides

Antimicrobial peptides (AMPs) are ancient and conserved across the tree of life. Their efficacy over evolutionary time has been largely attributed to their mechanisms of killing. Yet, the understanding of their pharmacodynamics both in vivo and in vitro is very limited. This is, however, crucial for applications of AMPs as drugs and also informs the understanding of the action of AMPs in natural immune systems. Here, we selected six different AMPs from different organisms to test their individual and combined effects in vitro. We analyzed their pharmacodynamics based on the Hill function and evaluated the interaction of combinations of two and three AMPs. Interactions of AMPs in our study were mostly synergistic, and three-AMP combinations displayed stronger synergism than two-AMP combinations. This suggests synergism to be a common phenomenon in AMP interaction. Additionally, AMPs displayed a sharp increase in killing within a narrow dose range, contrasting with those of antibiotics. We suggest that our results could lead a way toward better evaluation of AMP application in practice and shed some light on the evolutionary consequences of antimicrobial peptide interactions within the immune system of organisms

Resistance Evolution Against Antimicrobial Peptides in Staphylococcus aureus Alters Pharmacodynamics Beyond the MIC

Antimicrobial peptides (AMPs) have been proposed as a promising class of new antimicrobials partly because they are less susceptible to bacterial resistance evolution. This is possibly caused by their mode of action but also by their pharmacodynamic characteristics, which differ significantly from conventional antibiotics. Although pharmacodynamics of antibiotic resistant strains have been studied, such data are lacking for AMP resistant strains. Here, we investigated if the pharmacodynamics of the Gram-positive human pathogen Staphylococcous aureus evolve under antimicrobial peptide selection. Interestingly, the Hill coefficient (kappa κ) evolves together with the minimum inhibition concentration (MIC). Except for one genotype, strains harboring mutations in menF and atl, all mutants had higher kappa than the non-selected sensitive controls. Higher κ results in steeper pharmacodynamic curve and, importantly, in a narrower mutant selection window. S. aureus selected for resistance to melittin displayed cross resistant against pexiganan and had as steep pharmacodynamic curves (high κ) as pexiganan-selected lines. By contrast, the pexiganan-sensitive tenecin-selected lines displayed lower κ. Taken together, our data demonstrate that pharmacodynamic parameters are not fixed traits of particular drug/strain interactions but actually evolve under drug treatment. The contribution of factors such as κ and the maximum and minimum growth rates on the dynamics and probability of resistance evolution are open questions that require urgent attention

Current understanding of osteoarthritis pathogenesis and relevant new approaches

Osteoarthritis (OA) is the most common degenerative joint disease that causes painful swelling and permanent damage to the joints in the body. The molecular mechanisms of OA are currently unknown. OA is a heterogeneous disease that affects the entire joint, and multiple tissues are altered during OA development. To better understand the pathological mechanisms of OA, new approaches, methods, and techniques need to be used to understand OA pathogenesis. In this review, we first focus on the epigenetic regulation of OA, with a particular focus on DNA methylation, histone modification, and microRNA regulation, followed by a summary of several key mediators in OA-associated pain. We then introduce several innovative techniques that have been and will continue to be used in the fields of OA and OA-associated pain, such as CRISPR, scRNA sequencing, and lineage tracing. Next, we discuss the timely updates concerning cell death regulation in OA pathology, including pyroptosis, ferroptosis, and autophagy, as well as their individual roles in OA and potential molecular targets in treating OA. Finally, our review highlights new directions on the role of the synovial lymphatic system in OA. An improved understanding of OA pathogenesis will aid in the development of more specific and effective therapeutic interventions for OA

Critical Role of Activating Transcription Factor 4 in the Anabolic Actions of Parathyroid Hormone in Bone

Parathyroid hormone (PTH) is a potent anabolic agent for the treatment of osteoporosis. However, its mechanism of action in osteoblast and bone is not well understood. In this study, we show that the anabolic actions of PTH in bone are severely impaired in both growing and adult ovariectomized mice lacking bone-related activating transcription factor 4 (ATF4). Our study demonstrates that ATF4 deficiency suppresses PTH-stimulated osteoblast proliferation and survival and abolishes PTH-induced osteoblast differentiation, which, together, compromise the anabolic response. We further demonstrate that the PTH-dependent increase in osteoblast differentiation is correlated with ATF4-dependent up-regulation of Osterix. This regulation involves interactions of ATF4 with a specific enhancer sequence in the Osterix promoter. Furthermore, actions of PTH on Osterix require this same element and are associated with increased binding of ATF4 to chromatin. Taken together these experiments establish a fundamental role for ATF4 in the anabolic actions of PTH on the skeleton

A genome-wide association study of coat color in Chinese Rex rabbits

Coat color is an important phenotypic characteristic of the domestic rabbit (Oryctolagus cuniculus) and has specific economic importance in the Rex rabbit industry. Coat color varies considerably among different populations of rabbits, and several causal genes for this variation have been thoroughly studied. Nevertheless, the candidate genes affecting coat color variation in Chinese Rex rabbits remained to be investigated. In this study, we collected blood samples from 250 Chinese Rex rabbits with six different coat colors. We performed genome sequencing using a restriction site-associated DNA sequencing approach. A total of 91,546 single nucleotide polymorphisms (SNPs), evenly distributed among 21 autosomes, were identified. Genome-wide association studies (GWAS) were performed using a mixed linear model, in which the individual polygenic effect was fitted as a random effect. We detected a total of 24 significant SNPs that were located within a genomic region on chromosome 4 (OCU4). After re-fitting the most significant SNP (OCU4:13,434,448, p = 1.31e-12) as a covariate, another near-significant SNP (OCU4:11,344,946, p = 7.03e-07) was still present. Hence, we conclude that the 2.1-Mb genomic region located between these two significant SNPs is significantly associated with coat color in Chinese Rex rabbits. The well-studied coat-color-associated agouti signaling protein (ASIP) gene is located within this region. Furthermore, low genetic differentiation was also observed among the six coat color varieties. In conclusion, our results confirmed that ASIP is a putative causal gene affecting coat color variation in Chinese Rex rabbits

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe

Antimikrobielle Peptide: Pharmakodynamik, kombinatorische Effekte und Resistenzentwicklung

Antimicrobial peptides (AMPs) are ancient and conserved across the tree of life. They are the most important components in immune system due to their distinct mechanisms of killing bacteria. In this thesis, a pharmacodynamic approach was taken to investigate why bacteria are less likely to develop resistance to the nature immune system, especially to one of its components AMPs. In this thesis, the combination effects of AMPs were firstly investigated. Six different AMPs from different organisms were selected to test their individual and combined effects in vitro. With an approach based on pharmacodynamics and Loewe additivity, the interactions of AMPs were found mostly synergistic. Three-AMP combinations displayed stronger synergism than two-AMP combinations. Additionally, AMPs displayed a sharp increase in killing within a narrow dose range contrasting with those of antibiotics. Followed by a theoretical study, the combination effect between AMPs was explored using mathematical model that captures the dynamics of attachment and detachment between AMPs and cell membrane. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. This bottom-up approach revealed that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected; Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials. The AMPs were found fundamentally different from antibiotics in their pharmacodynamic characteristics. This difference was further implemented within a theoretical framework to predict the evolution of resistance. The comparative analysis of resistance evolution demonstrated that pharmacodynamic differences all combine to produce a much lower probability that resistance will evolve against antimicrobial peptides. The finding can be generalized to all drugs with pharmacodynamics similar to AMPs. Pharmacodynamic concepts are familiar to most practitioners of medical microbiology, and data can be easily obtained for any drug or drug combination. The theoretical and conceptual framework is therefore widely applicable and can help avoid resistance evolution if implemented in antibiotic stewardship schemes or the rational choice of new drug candidates. Next, A model multiple-step mutations which can describe more complicated situation was used to simulate the resistance evolution in the treatment of antimicrobials. In this model, each mutant was captured by a set of pharmacodynamics. By monitoring the time of resistance emergence, simulations showed that mutants with medium increment of MIC will emerge earlier. Mutation with fitness cost will slow down the resistance evolution. The fitness cost in resistant mutants is likely to be compensated as lately as possible, otherwise will hinder the emergence of later fitter mutant and thus slows down the resistance evolution. For a given mutants, the shape of dose-response and maximal killing rate that can be achieved by antimicrobials nearly have no influence on the time of their emergence. Because of the emergence and selection of fitter mutant always happens in the subMIC of this mutant. It also showed that treatment strategy and pharmacokinetics do not affect the rage of concentration that select resistance. Taken together, the thesis highlights that pharmacodynamic parameters of antimicrobials plays a decisive role in resistance selection. This can be applied in screening for resistance- proof drugs. In addition, it also explains the evolution of innate immune system which usually produces a mixture of AMPs to fight against infections. For example, mixtures of AMPs show strong synergism and steeper dose response curves in their pharmacodynamics.Antimikrobielle Peptide (AMPs) sind ein ursprüngliches Merkmal, welches im Stammbaum des Lebens konserviert ist. Aufgrund ihrer besonderen Mechanismen, mit denen sie Bakterien abtöten, sind sie die wichtigsten Komponenten im Immunsystem. In dieser Arbeit wurde mit einem pharmakodynamischen Ansatz untersucht, warum Bakterien mit geringerer Wahrscheinlichkeit Resistenzen gegen das angeborene Immunsystem, insbesondere gegen AMPs, entwickeln. Zuerst wurde der Effekt der Kombination von AMPs getestet. Sechs verschiedene AMPs von verschiedenen Organismen wurden auserwählt um ihre individuellen und kombinatorischen Auswirkungen in vitro zu ermitteln. Mit einem Ansatz, welcher auf Pharmakodynamik und der Loewe Additivität basiert, zeigten sich größtenteils synergistische Interaktionen der AMPs. Kombinationen von drei AMPs zeigten stärkere Synergien als solche mit nur zwei Komponenten. Weiterhin wurde, im Gegensatz zu Antibiotika, ein deutlicher Anstieg im Abtöten von Bakterien innerhalb eines engen Dosierungsbereichs beobachtet. Im Folgenden wurde theoretisch der kombinatorische Effekt von AMPs mit einem mathematischen Modell untersucht, welches die Dynamiken von Bindung und Ablösen zwischen AMPs und Zellmembran berücksichtigt. In diesem Modell werden Bakterien als getötet betrachtet, wenn eine bestimmte Anzahl von Zielen von antimikrobiellen Peptiden angegriffen wurde. Dieser Bottom-up Ansatz zeigte, dass die Unabhängigkeit nach Bliss als Modell verwendet werden sollte, wenn keine Interaktion zwischen den antimikrobiellen Molekülen zu erwarten ist. Die Loewe Additivität hingegen beschreibt Szenarien in denen die AMPs dieselben Komponenten der Zelle angreifen und demnach nicht unabhängig voneinander agieren. Die Auswahl der additiven Bedingungen im Modell ist essentiell um Synergien oder Antagonismen von antimikrobiellen Peptiden zu bestimmen. Die phamakodynamischen Merkmale der AMPs erwiesen sich als fundamental unterschiedlich gegenüber denen von Antibiotika. Dieser Unterschied wurde weiterhin in einem theoretischen Rahmen zur Vorhersage der Evolution von Resistenzen angewendet. Die vergleichende Analyse der Resistenzevolution machte deutlich, dass die kombinierten pharmakodynamische Eigenschaften für eine geringere Wahrscheinlichkeit der Entwicklung von Resistenzen gegenüber AMPs sorgen. Das Ergebnis kann hinsichtlich aller Wirkstoffe mit ähnlichen Pharmakodynamiken wie AMPs verallgemeinert werden. Pharmakodynamische Konzepte sind den meisten Fachleuten in der medizinischen Mikrobiologie bekannt und Daten können einfach sowohl für beliebige einzelne, als auch für Kombinationen von Wirkstoffen ermittelt werden. Das theoretische Konzept ist demnach im breiten Rahmen anwendbar und kann helfen, Evolution von Resistenzen zu vermeiden, wenn es in Verwaltung von Antibiotika oder der Auswahl neuer potentieller Wirkstoffe berücksichtigt wird. Darüber hinaus wurde ein Modell mit mehrstufigen Mutationen verwendet, welches kompliziertere Situationen hinsichtlich der Resistenzevolution bei der Behandlung mit antimikrobiellen Peptiden simulieren kann. In diesem Modell wurde jeder Mutant mit einer Auswahl von Pharmakodynamiken erfasst. Indem der Zeitraum in dem sich Resistenzen entwickelt hatten, ermittelt wurde zeigten Simulationen dass Mutanten mit einem mittleren Zuwachs in der MIC früher hervortraten. Mutationen mit Fitnesskosten verlangsamen die Resistenzevolution. Die Fitnesskosten in resistenten Mutanten werden höchstwahrscheinlich so spät wie möglich kompensiert, da sie ansonsten das Auftreten der späteren, fitteren Mutanten verhindern und die Evolution von Resistenzen verlangsamen würden. Für gegebene Mutanten haben die Reaktionen auf die Dosierung und die maximale Tötungsrate, welche mit antimikrobiellen Peptiden erreicht werden können, fast keinen Einfluss auf den Zeitpunkt ihres Auftretens. Dies kann dadurch erklärt werden, dass das Auftreten und die Selektion von fitteren Mutanten immer in im subMIC-Bereich des jeweiligen Mutanten passiert. Auch wurde verdeutlicht, dass Behandlungsstrategie und Pharmakokinetik keinen Einfluss auf das Konzentrationsspektrum, in dem auf Resistenzen selektiert wird, haben. Zusammengenommen betont die vorliegende Arbeit, dass pharmakodynamische Parameter von antimikrobiellen Peptiden eine entschiedene Rolle in der Selektion von Resistenzen spielen. Die Ergebnisse können in der Auswahl von resistenzsicheren Wirkstoffen Anwendung finden. Weiterhin liefern sie Erklärungen für die Evolution von angeborenen Immunsystemen, welche normalerweise einen Mix an AMPs im Kampf gegen Infektionen produzieren. Beispielsweise zeigen Mixe von AMPs starke Synergien und steilere Dosis- Reaktions-Kurven in ihrer Pharmakodynamik

Microstructure variation and growth mechanism of hypoeutectic Al-Si alloy solidifi ed under high pressure

The microstructure of hypoeutectic Al-9.21wt.%Si alloy solidified under 5.5 GPa was studied. The results show that the solidifi cation microstructure is refi ned. The primary α phase is the extended solid solution. The solid solubility of Si in α phase is up to 8.26wt.%. The growth mode of the α phase is cellular, and this cellular growth mechanism is interpreted in terms of the decrease of the diffusivity and the extended solid solution under high pressure. By calculation, it can be known that the the diffusivity of solute in the liquid under normal pressure is as high as two hundred times that under high pressure. The microhardness of the hypoeutectic Al-Si alloy solidified under high pressure is higher than that of solidifi ed under normal pressure. After annealing, Si precipitates from the solid solution, the microhardness of the alloy decrease, but, still higher than that of solidifi ed under normal pressure

The Evolution of Glycoside Hydrolase Family 1 in Insects Related to Their Adaptation to Plant Utilization

Insects closely interact with plants with multiple genes involved in their interactions. &beta;-glucosidase, constituted mainly by glycoside hydrolase family 1 (GH1), is a crucial enzyme in insects to digest plant cell walls and defend against natural enemies with sequestered plant metabolites. To gain more insights into the role of this enzyme in plant&ndash;insect interactions, we analyzed the evolutionary history of the GH1 gene family with publicly available insect genomes. We found that GH1 is widely present in insects, while the gene numbers are significantly higher in insect herbivores directly feeding on plant cell walls than in other insects. After reconciling the insect GH1 gene tree with a species tree, we found that the patterns of duplication and loss of GH1 genes differ among insect orders, which may be associated with the evolution of their ecology. Furthermore, the majority of insects&rsquo; GH1 genes were tandem-duplicated and subsequently went through neofunctionalization. This study shows the evolutionary history of an important gene family GH1 in insects and facilitates our understanding of the evolution of insect&ndash;plant interactions