Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward.

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

D-LMBmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry.

Recent proliferation and integration of tissue-clearing methods and light-sheet fluorescence microscopy has created new opportunities to achieve mesoscale three-dimensional whole-brain connectivity mapping with exceptionally high throughput. With the rapid generation of large, high-quality imaging datasets, downstream analysis is becoming the major technical bottleneck for mesoscale connectomics. Current computational solutions are labor intensive with limited applications because of the exhaustive manual annotation and heavily customized training. Meanwhile, whole-brain data analysis always requires combining multiple packages and secondary development by users. To address these challenges, we developed D-LMBmap, an end-to-end package providing an integrated workflow containing three modules based on deep-learning algorithms for whole-brain connectivity mapping: axon segmentation, brain region segmentation and whole-brain registration. D-LMBmap does not require manual annotation for axon segmentation and achieves quantitative analysis of whole-brain projectome in a single workflow with superior accuracy for multiple cell types in all of the modalities tested.

Inactivation of Malic Enzyme 1 in Endothelial Cells Alleviates Pulmonary Hypertension.

BACKGROUND: Pulmonary hypertension (PH) is a progressive cardiopulmonary disease with a high mortality rate. Although growing evidence has revealed the importance of dysregulated energetic metabolism in the pathogenesis of PH, the underlying cellular and molecular mechanisms are not fully understood. In this study, we focused on ME1 (malic enzyme 1), a key enzyme linking glycolysis to the tricarboxylic acid cycle. We aimed to determine the role and mechanistic action of ME1 in PH. METHODS: Global and endothelial-specific ME1 knockout mice were used to investigate the role of ME1 in hypoxia- and SU5416/hypoxia (SuHx)-induced PH. Small hairpin RNA and ME1 enzymatic inhibitor (ME1*) were used to study the mechanism of ME1 in pulmonary artery endothelial cells. Downstream key metabolic pathways and mediators of ME1 were identified by metabolomics analysis in vivo and ME1-mediated energetic alterations were examined by Seahorse metabolic analysis in vitro. The pharmacological effect of ME1* on PH treatment was evaluated in PH animal models induced by SuHx. RESULTS: We found that ME1 protein level and enzymatic activity were highly elevated in lung tissues of patients and mice with PH, primarily in vascular endothelial cells. Global knockout of ME1 protected mice from developing hypoxia- or SuHx-induced PH. Endothelial-specific ME1 deletion similarly attenuated pulmonary vascular remodeling and PH development in mice, suggesting a critical role of endothelial ME1 in PH. Mechanistic studies revealed that ME1 inhibition promoted downstream adenosine production and activated A2AR-mediated adenosine signaling, which leads to an increase in nitric oxide generation and a decrease in proinflammatory molecule expression in endothelial cells. ME1 inhibition activated adenosine production in an ATP-dependent manner through regulating malate-aspartate NADH (nicotinamide adenine dinucleotide plus hydrogen) shuttle and thereby balancing oxidative phosphorylation and glycolysis. Pharmacological inactivation of ME1 attenuated the progression of PH in both preventive and therapeutic settings by promoting adenosine production in vivo. CONCLUSIONS: Our findings indicate that ME1 upregulation in endothelial cells plays a causative role in PH development by negatively regulating adenosine production and subsequently dysregulating endothelial functions. Our findings also suggest that ME1 may represent as a novel pharmacological target for upregulating protective adenosine signaling in PH therapy.

Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss.

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss.

Meta-analysis of the global distribution of clinically relevant CYP2C8 alleles and their inferred functional consequences.

BACKGROUND: CYP2C8 is responsible for the metabolism of 5% of clinically prescribed drugs, including antimalarials, anti-cancer and anti-inflammatory drugs. Genetic variability is an important factor that influences CYP2C8 activity and modulates the pharmacokinetics, efficacy and safety of its substrates. RESULTS: We profiled the genetic landscape of CYP2C8 variability using data from 96 original studies and data repositories that included a total of 33,185 unrelated participants across 44 countries and 43 ethnic groups. The reduced function allele CYP2C8*2 was most common in West and Central Africa with frequencies of 16-36.9%, whereas it was rare in Europe and Asia (< 2%). In contrast, CYP2C8*3 and CYP2C8*4 were common throughout Europe and the Americas (6.9-19.8% for *3 and 2.3-7.5% for *4), but rare in African and East Asian populations. Importantly, we observe pronounced differences (> 2.3-fold) between neighboring countries and even between geographically overlapping populations. Overall, we found that 20-60% of individuals in Africa and Europe carry at least one CYP2C8 allele associated with reduced metabolism and increased adverse event risk of the anti-malarial amodiaquine. Furthermore, up to 60% of individuals of West African ancestry harbored variants that reduced the clearance of pioglitazone, repaglinide, paclitaxel and ibuprofen. In contrast, reduced function alleles are only found in < 2% of East Asian and 8.3-12.8% of South and West Asian individuals. CONCLUSIONS: Combined, the presented analyses mapped the genetic and inferred functional variability of CYP2C8 with high ethnogeographic resolution. These results can serve as a valuable resource for CYP2C8 allele frequencies and distribution estimates of CYP2C8 phenotypes that could help identify populations at risk upon treatment with CYP2C8 substrates. The high variability between ethnic groups incentivizes high-resolution pharmacogenetic profiling to guide precision medicine and maximize its socioeconomic benefits, particularly for understudied populations with distinct genetic profiles.

Organotypic and Microphysiological Human Tissue Models for Drug Discovery and Development-Current State-of-the-Art and Future Perspectives.

The number of successful drug development projects has been stagnant for decades despite major breakthroughs in chemistry, molecular biology, and genetics. Unreliable target identification and poor translatability of preclinical models have been identified as major causes of failure. To improve predictions of clinical efficacy and safety, interest has shifted to three-dimensional culture methods in which human cells can retain many physiologically and functionally relevant phenotypes for extended periods of time. Here, we review the state of the art of available organotypic culture techniques and critically review emerging models of human tissues with key importance for pharmacokinetics, pharmacodynamics, and toxicity. In addition, developments in bioprinting and microfluidic multiorgan cultures to emulate systemic drug disposition are summarized. We close by highlighting important trends regarding the fabrication of organotypic culture platforms and the choice of platform material to limit drug absorption and polymer leaching while supporting the phenotypic maintenance of cultured cells and allowing for scalable device fabrication. We conclude that organotypic and microphysiological human tissue models constitute promising systems to promote drug discovery and development by facilitating drug target identification and improving the preclinical evaluation of drug toxicity and pharmacokinetics. There is, however, a critical need for further validation, benchmarking, and consolidation efforts ideally conducted in intersectoral multicenter settings to accelerate acceptance of these novel models as reliable tools for translational pharmacology and toxicology. SIGNIFICANCE STATEMENT: Organotypic and microphysiological culture of human cells has emerged as a promising tool for preclinical drug discovery and development that might be able to narrow the translation gap. This review discusses recent technological and methodological advancements and the use of these systems for hit discovery and the evaluation of toxicity, clearance, and absorption of lead compounds.

Population-specific variations in KCNH2 predispose patients to delayed ventricular repolarization upon dihydroartemisinin-piperaquine therapy.

Dihydroartemisinin-piperaquine is efficacious for the treatment of uncomplicated malaria and its use is increasing globally. Despite the positive results in fighting malaria, inhibition of the Kv11.1 channel (hERG; encoded by the KCNH2 gene) by piperaquine has raised concerns about cardiac safety. Whether genetic factors could modulate the risk of piperaquine-mediated QT prolongations remained unclear. Here, we first profiled the genetic landscape of KCNH2 variability using data from 141,614 individuals. Overall, we found 1,007 exonic variants distributed over the entire gene body, 555 of which were missense. By optimizing the gene-specific parametrization of 16 partly orthogonal computational algorithms, we developed a KCNH2-specific ensemble classifier that identified a total of 116 putatively deleterious missense variations. To evaluate the clinical relevance of KCNH2 variability, we then sequenced 293 Malian patients with uncomplicated malaria and identified 13 variations within the voltage sensing and pore domains of Kv11.1 that directly interact with channel blockers. Cross-referencing of genetic and electrocardiographic data before and after piperaquine exposure revealed that carriers of two common variants, rs1805121 and rs41314375, experienced significantly higher QT prolongations (ΔQTc of 41.8 ms and 61 ms, respectively, vs 14.4 ms in controls) with more than 50% of carriers having increases in QTc >30 ms. Furthermore, we identified three carriers of rare population-specific variations who experienced clinically relevant delayed ventricular repolarization. Combined, our results map population-scale genetic variability of KCNH2 and identify genetic biomarkers for piperaquine-induced QT prolongation that could help to flag at-risk patients and optimize efficacy and adherence to antimalarial therapy.

APF2: an improved ensemble method for pharmacogenomic variant effect prediction.

Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.

Global distribution of functionally important CYP2C9 alleles and their inferred metabolic consequences.

BACKGROUND: Genetic variability in the cytochrome P450 CYP2C9 constitutes an important predictor for efficacy and safety of various commonly prescribed drugs, including coumarin anticoagulants, phenytoin and multiple non-steroidal anti-inflammatory drugs (NSAIDs). A global map of CYP2C9 variability and its inferred functional consequences has been lacking. RESULTS: Frequencies of eight functionally relevant CYP2C9 alleles (*2, *3, *5, *6, *8, *11, *13 and *14) were analyzed. In total, 108 original articles were identified that included genotype data from a total of 81,662 unrelated individuals across 70 countries and 40 unique ethnic groups. The results revealed that CYP2C9*2 was most abundant in Europe and the Middle East, whereas CYP2C9*3 was the main reason for reduced CYP2C9 activity across South Asia. Our data show extensive variation within superpopulations with up to tenfold differences between geographically adjacent populations in Malaysia, Thailand and Vietnam. Translation of genetic CYP2C9 variability into functional consequences indicates that up to 40% of patients in Southern Europe and the Middle East might benefit from warfarin and phenytoin dose reductions, while 3% of patients in Southern Europe and Israel are recommended to reduce starting doses of NSAIDs. CONCLUSIONS: This study provides a comprehensive map of the genetic and functional variability of CYP2C9 with high ethnogeographic resolution. The presented data can serve as a useful resource for CYP2C9 allele and phenotype frequencies and might guide the optimization of genotyping strategies, particularly for indigenous and founder populations with distinct genetic profiles.

Adenovirus-mediated Overexpression of FcγRIIB Attenuates Pulmonary Inflammation and Fibrosis.

Progressive fibrosing interstitial lung diseases (PF-ILDs) result in high mortality and lack effective therapies. The pathogenesis of PF-ILDs involves macrophages driving inflammation and irreversible fibrosis. Fc-γ receptors (FcγRs) regulate macrophages and inflammation, but their roles in PF-ILDs remain unclear. We characterized the expression of FcγRs and found upregulated FcγRIIB in human and mouse lungs after exposure to silica. FcγRIIB deficiency aggravated lung dysfunction, inflammation, and fibrosis in silica-exposed mice. Using single-cell transcriptomics and in vitro experiments, FcγRIIB was found in alveolar macrophages, where it regulated the expression of fibrosis-related genes Spp1 and Ctss. In mice with macrophage-specific overexpression of FcγRIIB and in mice treated with adenovirus by intratracheal instillation to upregulate FcγRIIB, silica-induced functional and histological changes were ameliorated. Our data from three genetic models and a therapeutic model suggest that FcγRIIB plays a protective role that can be enhanced by adenoviral overexpression, representing a potential therapeutic strategy for PF-ILDs.

Eosinophils protect against pulmonary hypertension through 14-HDHA and 17-HDHA.

BACKGROUND: Pulmonary hypertension (PH) is a life-threatening disease featuring pulmonary vessel remodelling and perivascular inflammation. The effect, if any, of eosinophils (EOS) on the development of PH remains unclear. METHODS: EOS infiltration and chemotaxis were investigated in peripheral blood and lung tissues from pulmonary arterial hypertension (PAH) patients without allergic history and from sugen/hypoxia-induced PH mice. The role of EOS deficiency in PH development was investigated using GATA1-deletion (ΔdblGATA) mice and anti-interleukin 5 antibody-treated mice and rats. Ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was conducted to identify the critical oxylipin molecule(s) produced by EOS. Culture supernatants and lysates of EOS were collected to explore the mechanisms in co-culture cell experiments. RESULTS: There was a lower percentage of EOS in peripheral blood but higher infiltration in lung tissues from PAH patients and PH mice. PAH/PH lungs showed increased EOS-related chemokine expression, mainly C-C motif chemokine ligand 11 derived from adventitial fibroblasts. EOS deficiency aggravated PH in rodents, accompanied by increased neutrophil and monocyte/macrophage infiltration. EOS highly expressed arachidonate 15-lipoxygenase (ALOX15). 14-hydroxy docosahexaenoic acid (14-HDHA) and 17-HDHA were critical downstream oxylipins produced by EOS, which showed anti-inflammatory effects on recruitment of neutrophils and monocytes/macrophages through N-formyl peptide receptor 2. They also repressed pulmonary artery smooth muscle cell (PASMC) proliferation by activating peroxisome proliferator-activated receptor γ and blunting Stat3 phosphorylation. CONCLUSIONS: In PH development without external stimuli, peripheral blood exhibits a low EOS level. EOS play a protective role by suppressing perivascular inflammation and maintaining PASMC homeostasis via 14/17-HDHA.

Translating pharmacogenomic sequencing data into drug response predictions-How to interpret variants of unknown significance.

The rapid development of sequencing technologies during the past 20 years has provided a variety of methods and tools to interrogate human genomic variations at the population level. Pharmacogenes are well known to be highly polymorphic and a plethora of pharmacogenomic variants has been identified in population sequencing data. However, so far only a small number of these variants have been functionally characterized regarding their impact on drug efficacy and toxicity and the significance of the vast majority remains unknown. It is therefore of high importance to develop tools and frameworks to accurately infer the effects of pharmacogenomic variants and, eventually, aggregate the effect of individual variations into personalized drug response predictions. To address this challenge, we here first describe the technological advances, including sequencing methods and accompanying bioinformatic processing pipelines that have enabled reliable variant identification. Subsequently, we highlight advances in computational algorithms for pharmacogenomic variant interpretation and discuss the added value of emerging strategies, such as machine learning and the integrative use of omics techniques that have the potential to further contribute to the refinement of personalized pharmacological response predictions. Lastly, we provide an overview of experimental and clinical approaches to validate in silico predictions. We conclude that the iterative feedback between computational predictions and experimental validations is likely to rapidly improve the accuracy of pharmacogenomic prediction models, which might soon allow for an incorporation of the entire pharmacogenetic profile into personalized response predictions.

Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy.

Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.

Population pharmacogenomics: an update on ethnogeographic differences and opportunities for precision public health.

Both safety and efficacy of medical treatment can vary depending on the ethnogeographic background of the patient. One of the reasons underlying this variability is differences in pharmacogenetic polymorphisms in genes involved in drug disposition, as well as in drug targets. Knowledge and appreciation of these differences is thus essential to optimize population-stratified care. Here, we provide an extensive updated analysis of population pharmacogenomics in ten pharmacokinetic genes (CYP2D6, CYP2C19, DPYD, TPMT, NUDT15 and SLC22A1), drug targets (CFTR) and genes involved in drug hypersensitivity (HLA-A, HLA-B) or drug-induced acute hemolytic anemia (G6PD). Combined, polymorphisms in the analyzed genes affect the pharmacology, efficacy or safety of 141 different drugs and therapeutic regimens. The data reveal pronounced differences in the genetic landscape, complexity and variant frequencies between ethnogeographic groups. Reduced function alleles of CYP2D6, SLC22A1 and CFTR were most prevalent in individuals of European descent, whereas DPYD and TPMT deficiencies were most common in Sub-Saharan Africa. Oceanian populations showed the highest frequencies of CYP2C19 loss-of-function alleles while their inferred CYP2D6 activity was among the highest worldwide. Frequencies of HLA-B*15:02 and HLA-B*58:01 were highest across Asia, which has important implications for the risk of severe cutaneous adverse reactions upon treatment with carbamazepine and allopurinol. G6PD deficiencies were most frequent in Africa, the Middle East and Southeast Asia with pronounced differences in variant composition. These variability data provide an important resource to inform cost-effectiveness modeling and guide population-specific genotyping strategies with the goal of optimizing the implementation of precision public health.

The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data.

Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.

Novel loss-of-function variant in DENND5A impedes melanosomal cargo transport and predisposes to familial cutaneous melanoma.

PURPOSE: More than half of the familial cutaneous melanomas have unknown genetic predisposition. This study aims at characterizing a novel melanoma susceptibility gene. METHODS: We performed exome and targeted sequencing in melanoma-prone families without any known melanoma susceptibility genes. We analyzed the expression of candidate gene DENND5A in melanoma samples in relation to pigmentation and UV signature. Functional studies were carried out using microscopic approaches and zebrafish model. RESULTS: We identified a novel DENND5A truncating variant that segregated with melanoma in a Swedish family and 2 additional rare DENND5A variants, 1 of which segregated with the disease in an American family. We found that DENND5A is significantly enriched in pigmented melanoma tissue. Our functional studies show that loss of DENND5A function leads to decrease in melanin content in vitro and pigmentation defects in vivo. Mechanistically, harboring the truncating variant or being suppressed leads to DENND5A losing its interaction with SNX1 and its ability to transport the SNX1-associated vesicles from melanosomes. Consequently, untethered SNX1-premelanosome protein and redundant tyrosinase are redirected to lysosomal degradation by default, causing decrease in melanin content. CONCLUSION: Our findings provide evidence of a physiological role of DENND5A in the skin context and link its variants to melanoma susceptibility.

Identification and functional validation of novel pharmacogenomic variants using a next-generation sequencing-based approach for clinical pharmacogenomics.

Inter-individual variability in pharmacokinetics and drug response is heavily influenced by single-nucleotide variants (SNVs) and copy-number variations (CNVs) in genes with importance for drug disposition. Nowadays, a plethora of studies implement next generation sequencing to capture rare and novel pharmacogenomic (PGx) variants that influence drug response. To address these issues, we present a comprehensive end-to-end analysis workflow, beginning from targeted PGx panel re-sequencing to in silico analysis pipelines and in vitro validation assays. Specifically, we show that novel pharmacogenetic missense variants that are predicted or putatively predicted to be functionally deleterious, significantly alter protein activity levels of CYP2D6 and CYP2C19 proteins. We further demonstrate that variant priorization pipelines tailored with functional in vitro validation assays provide supporting evidence for the deleterious effect of novel PGx variants. The proposed workflow could provide the basis for integrating next-generation sequencing for PGx testing into routine clinical practice.

Zwitterionic surface chemistry enhances detachment of bacteria under shear.

The ubiquitous nature of microorganisms, especially of biofilm-forming bacteria, makes biofouling a prevalent challenge in many settings, including medical and industrial environments immersed in liquid and subjected to shear forces. Recent studies have shown that zwitterionic groups are effective in suppressing bacteria and protein adhesion as well as biofilm growth. However, the effect of zwitterionic groups on the removal of surface-bound bacteria has not been extensively studied. Here we present a microfluidic approach to evaluate the effectiveness in facilitating bacteria detachment by shear of an antifouling surface treatment using (3-(dimethyl;(3-trimethoxysilyl)propyl)ammonia propane-1-sulfonate), a sulfobetaine silane (SBS). Control studies show that SBS-functionalized surfaces greatly increase protein (bovine serum albumin) removal upon rinsing. On the same surfaces, enhanced bacteria (Pseudomonas aeruginosa) removal is observed under shear. To quantify this enhancement a microfluidic shear device is employed to investigate how SBS-functionalized surfaces promote bacteria detachment under shear. By using a microfluidic channel with five shear zones, we compare the removal of bacteria from zwitterionic and glass surfaces under different shear rates. At times of 15 min, 30 min, and 60 min, bacteria adhesion on SBS-functionalized surfaces is reduced relative to the control surface (glass) under quiescent conditions. However, surface-associated bacteria on the SBS-functionalized glass and control show similar percentages of live cells, suggesting minimal intrinsic biocidal effect from the SBS-functionalized surface. Notably, when exposed to shear rates ranging from 104 to 105 s-1, significantly fewer bacteria remain on the SBS-functionalized surfaces. These results demonstrate the potential of zwitterionic sulfobetaine as effective antifouling coatings that facilitate the removal of bacteria under shear.

Tetrandrine alleviates silicosis by inhibiting canonical and non-canonical NLRP3 inflammasome activation in lung macrophages.

Silicosis caused by inhalation of silica particles leads to more than ten thousand new occupational exposure-related deaths yearly. Exacerbating this issue, there are currently few drugs reported to effectively treat silicosis. Tetrandrine is the only drug approved for silicosis treatment in China, and despite more than decades of use, its efficacy and mechanisms of action remain largely unknown. Here, in this study, we established silicosis mouse models to investigate the effectiveness of tetrandrine of early and late therapeutic administration. To this end, we used multiple cardiopulmonary function test, as well as markers for inflammation and fibrosis. Moreover, using single cell RNA sequencing and transcriptomics of lung tissue and quantitative microarray analysis of serum from silicosis and control mice, our results provide a novel description of the target pathways for tetrandrine. Specifically, we found that tetrandrine attenuated silicosis by inhibiting both the canonical and non-canonical NLRP3 inflammasome pathways in lung macrophages. Taken together, our work showed that tetrandrine yielded promising results against silicosis-associated inflammation and fibrosis and further lied the groundwork for understanding its molecular targets. Our results also facilitated the wider adoption and development of tetrandirne, potentially accelerating a globally accepted therapeutic strategy for silicosis.

Pharmacogene Sequencing of a Gabonese Population with Severe Plasmodium falciparum Malaria Reveals Multiple Novel Variants with Putative Relevance for Antimalarial Treatment.

Malaria remains one of the deadliest diseases in Africa, particularly for children. While successful in reducing morbidity and mortality, antimalarial treatments are also a major cause of adverse drug reactions (ADRs). Host genetic variation in genes involved in drug disposition or toxicity constitutes an important determinant of ADR risk and can prime for parasite drug resistance. Importantly, however, the genetic diversity in Africa is substantial, and thus, genetic profiles in one population cannot be reliably extrapolated to other ethnogeographic groups. Gabon is considered a high-transmission country, with more than 460,000 malaria cases per year. Yet the pharmacogenetic landscape of the Gabonese population or its neighboring countries has not been analyzed. Using targeted sequencing, here, we profiled 21 pharmacogenes with importance for antimalarial treatment in 48 Gabonese pediatric patients with severe Plasmodium falciparum malaria. Overall, we identified 347 genetic variants, of which 18 were novel, and each individual was found to carry 87.3 ± 9.2 (standard deviation [SD]) variants across all analyzed genes. Importantly, 16.7% of these variants were population specific, highlighting the need for high-resolution pharmacogenomic profiling. Between one in three and one in six individuals harbored reduced-activity alleles of CYP2A6, CYP2B6, CYP2D6, and CYP2C8 with important implications for artemisinin, chloroquine, and amodiaquine therapy. Furthermore, one in three patients harbored at least one G6PD-deficient allele, suggesting a considerably increased risk of hemolytic anemia upon exposure to aminoquinolines. Combined, our results reveal the unique genetic landscape of the Gabonese population and pinpoint the genetic basis for interindividual differences in antimalarial drug responses and toxicity.