In Situ Infrared Spectroscopic Evidence of Enhanced Electrochemical CO2 Reduction and C-C Coupling on Oxide-Derived Copper.

The reaction mechanism of CO2 electroreduction on oxide-derived copper has not yet been unraveled even though high C2+ Faradaic efficiencies are commonly observed on these surfaces. In this study, we aim to explore the effects of copper anodization on the adsorption of various CO2RR intermediates using in situ surface-enhanced infrared absorption spectroscopy (SEIRAS) on metallic and mildly anodized copper thin films. The in situ SEIRAS results show that the preoxidation process can significantly improve the overall CO2 reduction activity by (1) enhancing CO2 activation, (2) increasing CO uptake, and (3) promoting C-C coupling. First, the strong *COO- redshift indicates that the preoxidation process significantly enhances the first elementary step of CO2 adsorption and activation. The rapid uptake of adsorbed *COatop also illustrates how a high *CO coverage can be achieved in oxide-derived copper electrocatalysts. Finally, for the first time, we observed the formation of the *COCHO dimer on the anodized copper thin film. Using DFT calculations, we show how the presence of subsurface oxygen within the Cu lattice can improve the thermodynamics of C2 product formation via the coupling of adsorbed *CO and *CHO intermediates. This study advances our understanding of the role of surface and subsurface conditions in improving the catalytic reaction kinetics and product selectivity of CO2 reduction.

Observation of Hidden Polar Phases and Flux Closure Domain Topology in Bi2WO6 Thin Films.

Topological textures of ferroelectric polarizations have promise as alternative devices for future information technology. A polarization rotation inevitably deviates from the stable orientation in axial ferroelectrics, but local energy losses compromise the global symmetry, resulting in a distorted shape of the topological vortex or inhibiting the vortex. Easy planar isotropy helps to promote rotating structures and, accordingly, to facilitate access to nontrivial textures. Here, we investigate the domain structure of an epitaxial thin film of bismuth tungsten oxide (Bi2WO6) grown on a (001) SrTiO3 substrate. By using angle-resolved piezoresponse force microscopy and scanning transmission electron microscopy, we find the existence of a hidden phase with ⟨100⟩-oriented ferroelectric polarizations in the middle of the four variant ⟨110⟩-oriented polarization domains, which assists in the formation of flux closure domains. The results suggest that this material is one step closer to becoming an isotropic two-dimensional polar material.

High-Performance Ammonia Electrosynthesis from Nitrate in a NaOH-KOH-H2O Ternary Electrolyte.

A glut of dinitrogen-derived ammonia (NH3) over the past century has resulted in a heavily imbalanced nitrogen cycle and consequently, the large-scale accumulation of reactive nitrogen such as nitrates in our ecosystems has led to detrimental environmental issues. Electrocatalytic upcycling of waste nitrogen back into NH3 holds promise in mitigating these environmental impacts and reducing reliance on the energy-intensive Haber-Bosch process. Herein, we report a high-performance electrolyzer using an ultrahigh alkalinity electrolyte, NaOH-KOH-H2O, for low-cost NH3 electrosynthesis. At 3,000 mA/cm2, the device with a Fe-Cu-Ni ternary catalyst achieves an unprecedented faradaic efficiency (FE) of 92.5±1.5 % under a low cell voltage of 3.83 V; whereas at 1,000 mA/cm2, an FE of 96.5±4.8 % under a cell voltage of only 2.40 V was achieved. Techno-economic analysis revealed that our device cuts the levelized cost of ammonia electrosynthesis by ~40 % ($30.68 for Fe-Cu-Ni vs. $48.53 for Ni foam per kmol-NH3). The NaOH-KOH-H2O electrolyte together with the Fe-Cu-Ni ternary catalyst can enable the high-throughput nitrate-to-ammonia applications for affordable and scalable real-world wastewater treatments.

Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma.

An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.

Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology.

Patient-based cancer models are essential tools for studying tumor biology and for the assessment of drug responses in a translational context. We report the establishment a large cohort of unique organoids and patient-derived orthotopic xenografts (PDOX) of various glioma subtypes, including gliomas with mutations in IDH1, and paired longitudinal PDOX from primary and recurrent tumors of the same patient. We show that glioma PDOXs enable long-term propagation of patient tumors and represent clinically relevant patient avatars that retain histopathological, genetic, epigenetic, and transcriptomic features of parental tumors. We find no evidence of mouse-specific clonal evolution in glioma PDOXs. Our cohort captures individual molecular genotypes for precision medicine including mutations in IDH1, ATRX, TP53, MDM2/4, amplification of EGFR, PDGFRA, MET, CDK4/6, MDM2/4, and deletion of CDKN2A/B, PTCH, and PTEN. Matched longitudinal PDOX recapitulate the limited genetic evolution of gliomas observed in patients following treatment. At the histological level, we observe increased vascularization in the rat host as compared to mice. PDOX-derived standardized glioma organoids are amenable to high-throughput drug screens that can be validated in mice. We show clinically relevant responses to temozolomide (TMZ) and to targeted treatments, such as EGFR and CDK4/6 inhibitors in (epi)genetically defined subgroups, according to MGMT promoter and EGFR/CDK status, respectively. Dianhydrogalactitol (VAL-083), a promising bifunctional alkylating agent in the current clinical trial, displayed high therapeutic efficacy, and was able to overcome TMZ resistance in glioblastoma. Our work underscores the clinical relevance of glioma organoids and PDOX models for translational research and personalized treatment studies and represents a unique publicly available resource for precision oncology.

Precision medicine approaches to lung adenocarcinoma with concomitant MET and HER2 amplification.

BACKGROUND: Patient-derived xenograft (PDX) models are important tools in precision medicine and for the development of targeted therapies to treat cancer patients. This study aimed to evaluate our precision medicine strategy that integrates genomic profiling and preclinical drug-screening platforms, in order to personalize cancer treatments using PDX models. METHODS: We performed array-comparative genomic hybridization, microarray, and targeted next-generation sequencing analyses, in order to determine the oncogenic driver mutations. PDX cells were obtained from PDXs and subsequently screened in vitro with 17 targeted agents. RESULTS: PDX tumors recapitulated the histopathologic and genetic features of the patient tumors. Among the samples from lung cancer patients that were molecularly-profiled, copy number analysis identified unique focal MET amplification in one sample, 033 T, without RTK/RAS/RAF oncogene mutations. Although HER2 amplification in 033 T was not detected in the cancer panel, the selection of HER2-amplified clones was found in PDXs and PDX cells. Additionally, MET and HER2 overexpression were found in patient tumors, PDXs, and PDX cells. Crizotinib or EGFR tyrosine kinase inhibitor treatments significantly inhibited cell growth and impaired tumor sphere formation in 033 T PDX cells. CONCLUSIONS: We established PDX cell models using surgical samples from lung cancer patients, and investigated their preclinical and clinical implications for personalized targeted therapy. Additionally, we suggest that MET and EGFR inhibitor-based therapy can be used to treat MET and HER2-overexpressing lung cancers, without receptor tyrosine kinase /RAS/RAF pathway alterations.

Proteomic-based approach to gain insight into reprogramming of THP-1 cells exposed to Leishmania donovani over an early temporal window.

Leishmania donovani, a protozoan parasite, is the causative agent of visceral leishmaniasis. It lives and multiplies within the harsh environment of macrophages. In order to investigate how intracellular parasite manipulate the host cell environment, we undertook a quantitative proteomic study of human monocyte-derived macrophages (THP-1) following infection with L. donovani. We used the isobaric tags for relative and absolute quantification (iTRAQ) method and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to compare expression profiles of noninfected and L. donovani-infected THP-1 cells. We detected modifications of protein expression in key metabolic pathways, including glycolysis and fatty acid oxidation, suggesting a global reprogramming of cell metabolism by the parasite. An increased abundance of proteins involved in gene transcription, RNA splicing (heterogeneous nuclear ribonucleoproteins [hnRNPs]), histones, and DNA repair and replication was observed at 24 h postinfection. Proteins involved in cell survival and signal transduction were more abundant at 24 h postinfection. Several of the differentially expressed proteins had not been previously implicated in response to the parasite, while the others support the previously identified proteins. Selected proteomics results were validated by real-time PCR and immunoblot analyses. Similar changes were observed in L. donovani-infected human monocyte-derived primary macrophages. The effect of RNA interference (RNAi)-mediated gene knockdown of proteins validated the relevance of the host quantitative proteomic screen. Our findings indicate that the host cell proteome is modulated after L. donovani infection, provide evidence for global reprogramming of cell metabolism, and demonstrate the complex relations between the host and parasite at the molecular level.

Identification of human host factors required for beta-defensin-2 expression in intestinal epithelial cells upon a bacterial challenge.

The human intestinal tract is colonized with microorganisms, which present a diverse array of immunological challenges. A number of antimicrobial mechanisms have evolved to cope with these challenges. A key defense mechanism is the expression of inducible antimicrobial peptides (AMPs), such as beta-defensins, which rapidly inactivate microorganisms. We currently have a limited knowledge of mechanisms regulating the inducible expression of AMP genes, especially factors from the host required in these regulatory mechanisms. To identify the host factors required for expression of the beta-defensin-2 gene (HBD2) in intestinal epithelial cells upon a bacterial challenge, we performed a RNAi screen using a siRNA library spanning the whole human genome. The screening was performed in duplicate to select the strongest 79 and 110 hit genes whose silencing promoted or inhibited HBD2 expression, respectively. A set of 57 hits selected among the two groups of genes was subjected to a counter-screening and a subset was subsequently validated for its impact onto HBD2 expression. Among the 57 confirmed hits, we brought out the TLR5-MYD88 signaling pathway, but above all new signaling proteins, epigenetic regulators and transcription factors so far unrevealed in the HBD2 regulatory circuits, like the GATA6 transcription factor involved in inflammatory bowel diseases. This study represents a significant step toward unveiling the key molecular requirements to promote AMP expression in human intestinal epithelial cells, and revealing new potential targets for the development of an innovative therapeutic strategy aiming at stimulating the host AMP expression, at the era of antimicrobial resistance.

CT109-SN-38, a Novel Antibody-drug Conjugate with Dual Specificity for CEACAM5 and 6, Elicits Potent Killing of Pancreatic Cancer Cells.

BACKGROUND: CEACAM5 and CEACAM6 are glycosylphosphatidylinositol (GPI)- linked members of the carcinoembryonic antigen-related cell adhesion molecule (CEACAM) family, which are frequently upregulated in epithelial cancers where they contribute to invasion, metastasis, immune evasion, and resistance to anoikis. CT109 is a novel antibody with dual specificity to both CEACAM5 and 6. OBJECTIVES: In this study, we aimed to perform the preclinical characterization of CT109 and antibody- drug conjugate (ADCs) derivatives of CT109, focusing on CT109-SN-38. METHODS: CT109's cognate epitope was characterized by scanning mutagenesis. CT109 specificity and internalization kinetics were assessed by immunoblot and flow cytometry, respectively. Cognate antigen expression prevalence in colorectal cancer and normal tissue arrays was determined by immunohistochemistry. CT109 conjugations were generated by the reaction of reduced CT109 cysteines with maleimide-functionalized payload linkers. In vitro cytotoxic activity of CT109 ADCs was characterized on antigen-positive and negative pancreatic ductal adenocarcinoma cell (PDAC) lines using a luminometric viability assay. In vivo efficacy of CT109-SN-38 was assessed on a PDAC tumor xenograft model at 10 and 25 mg/kg concentrations. RESULTS: CT109 was shown to bind a glycoepitope centered on N309. CT109 is internalized in the CEACAM5+/CEACAM6+ double-positive PDAC line, BxPC-3, with a t1/2 of 2.3 hours. CT109 ADCs elicit a dose and antigen-dependent cytotoxic effect, with CT109-SN-38 exhibiting an IC50 value of 21 nM in BxPC-3 cells. In a BxPC-3 tumor xenograft model, CT109-SN-38 reduced tumor growth and induced regression in 3/10 mice at a concentration 25 mg/kg. CONCLUSION: These data suggest that further preclinical and clinical development of CT109-SN-38 is warranted.

Prediction of TKI response in EGFR-mutant lung cancer patients-derived organoids using malignant pleural effusion.

Patient-derived organoids (PDOs) are valuable in predicting response to cancer therapy. PDOs are ideal models for precision oncologists. However, their practical application in guiding timely clinical decisions remains challenging. This study focused on patients with advanced EGFR-mutated non-small cell lung cancer and employed a cancer organoid-based diagnosis reactivity prediction (CODRP)-based precision oncology platform to assess the efficacy of EGFR inhibitor treatments. CODRP was employed to evaluate EGFR-tyrosine kinase inhibitors (TKI) drug sensitivity. The results were compared to those obtained using area under the curve index. This study validated this index by testing lung cancer-derived organoids in 14 patients with lung cancer. The CODRP index-based drug sensitivity test reliably classified patient responses to EGFR-TKI treatment within a clinically suitable 10-day timeline, which aligned with clinical drug treatment responses. This approach is promising for predicting and analyzing the efficacy of anticancer, ultimately contributing to the development of a precision medicine platform.

Revealing invisible cell phenotypes with conditional generative modeling.

Biological sciences, drug discovery and medicine rely heavily on cell phenotype perturbation and microscope observation. However, most cellular phenotypic changes are subtle and thus hidden from us by natural cell variability: two cells in the same condition already look different. In this study, we show that conditional generative models can be used to transform an image of cells from any one condition to another, thus canceling cell variability. We visually and quantitatively validate that the principle of synthetic cell perturbation works on discernible cases. We then illustrate its effectiveness in displaying otherwise invisible cell phenotypes triggered by blood cells under parasite infection, or by the presence of a disease-causing pathological mutation in differentiated neurons derived from iPSCs, or by low concentration drug treatments. The proposed approach, easy to use and robust, opens the door to more accessible discovery of biological and disease biomarkers.

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma.

BACKGROUND: Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. METHODS: We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. RESULTS: In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e-4 for progression-free survival (PFS) and 3.63e-4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher's exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e-4 for PFS and 3.66e-4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). CONCLUSIONS: We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

Quantum dot-based screening system for discovery of g protein-coupled receptor agonists.

Cellular imaging has emerged as an important tool to unravel biological complexity and to accelerate the drug-discovery process, including cell-based screening, target identification, and mechanism of action studies. Recently, semiconductor nanoparticles known as quantum dots (QDs) have attracted great interest in cellular imaging applications due to their unique photophysical properties such as size, tunable optical property, multiplexing capability, and photostability. Herein, we show that QDs can also be applied to assay development and eventually to high-throughput/content screening (HTS/HCS) for drug discovery. We have synthesized QDs modified with PEG and primary antibodies to be used as fluorescent probes for a cell-based HTS system. The G protein-coupled receptor (GPCR) family is known to be involved in most major diseases. We therefore constructed human osteosarcoma (U2OS) cells that specifically overexpress two types of differently tagged GPCRs: influenza hemagglutinin (HA) peptide-tagged κ-opioid receptors (κ-ORs) and GFP-tagged A3 adenosine receptors (A3AR). In this study, we have demonstrated that 1) anti-HA antibody-conjugated QDs could specifically label HA-tagged κ-ORs, 2) subsequent treatment of QD-tagged GPCR agonists allowed agonist-induced translocation to be monitored in real time, 3) excellent emission spectral properties of QD permitted the simultaneous detection of two GPCRs in one cell, and 4) the robust imaging capabilities of the QD-antibody conjugates could lead to reproducible quantitative data from high-content cellular images. These results suggest that the present QD-based GPCR inhibitor screening system can be a promising platform for further drug screening applications.

Simple Saliva Sample Collection for the Detection of SARS-CoV-2 Variants Compared With Nasopharyngeal Swab Sample.

CONTEXT.­: The use of saliva samples for diagnosis of SARS-CoV-2 infection offers several advantages, including ease of sample collection, feasibility of self-collection, and minimization of medical staff exposure to infection. The emergence of new SARS-CoV-2 variants has had an impact on the viral load of specimens and the results of real-time reverse transcription-polymerase chain reaction (rRT-PCR). OBJECTIVE.­: To compare nasopharyngeal swab and saliva samples for the diagnosis of SARS-CoV-2 using rRT-PCR. DESIGN.­: In this study, participants were recruited prospectively, and paired nasopharyngeal swab and saliva samples were collected simultaneously from each participant. After adding universal transport medium, RNA was extracted in an identical manner for both sample types, and samples were tested using rRT-PCR. In addition, samples with positive results were tested for SARS-CoV-2 variants. RESULTS.­: Of the 338 paired samples, 100 nasopharyngeal swab and 101 saliva samples tested positive for SARS-CoV-2. The rRT-PCR results of the saliva and nasopharyngeal swab samples showed a positive percent agreement of 95.0% (95% CI, 88.7%-98.4%), a negative percent agreement of 97.9% (95% CI, 95.2%-99.3%), and an overall percent agreement of 96.8% (95% CI, 94.3%-98.4%). SARS-CoV-2 was detected in the saliva samples of 6 participants with negative nasopharyngeal sample results. In addition, the sensitivity of saliva samples was similar to that of nasopharyngeal samples for detecting various SARS-CoV-2 variants, including the Omicron variant. CONCLUSIONS.­: Saliva samples can be used as an alternative to nasopharyngeal samples for convenient and effective detection of various SARS-CoV-2 variants.

High-content phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons using machine learning classification.

Combining multiple Parkinson's disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic neuron (mDAN) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control, and genetically unrelated iPSCs into mDANs. Using automated fluorescence microscopy in 384-well-plate format, we identified elevated levels of α-synuclein (αSyn) and serine 129 phosphorylation, reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDANs according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or αSyn levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient-derived SNCA gene triplication mDAN model which overexpresses αSyn. This phenotyping and classification strategy improves the practical exploitability of mDANs for disease modeling and the identification of novel LRRK2-associated drug targets.

Personalized functional profiling using ex-vivo patient-derived spheroids points out the potential of an antiangiogenic treatment in a patient with a metastatic lung atypical carcinoid.

Lung carcinoids are neuroendocrine tumors representing 1 to 2% of lung cancers. This study outlines the case of a patient with a metastatic lung atypical carcinoid who presented with a pleural effusion and progression of liver metastases after developing resistance to conventional treatments. Personalized functional profiling (PFP), i.e. drug screening, was performed in ex-vivo spheroids obtained from the patient's liver metastasis to identify potential therapeutic options. The drug screening results revealed cediranib, an antiangiogenic drug, as a hit drug for this patient, from a library of 66 Food and Drug Administration (FDA)-approved and investigational drugs. Based on the PFP results and the reported evidence of clinical efficacy of bevacizumab and capecitabine combination in gastro-intestinal neuroendocrine tumors, this combination was given to the patient. Four months later, the pleural effusion and pleura carcinosis regressed and the liver metastasis did not progress. The patient experienced 2 years of a stable disease under the PFP-guided personalized treatment.

Intracellular protein target detection by quantum dots optimized for live cell imaging.

Imaging of specific intracellular target proteins in living cells has been of great challenge and importance for understanding intracellular events and elucidating various biological phenomena. Highly photoluminescent and water-soluble semiconductor nanocrystal quantum dots (QDs) have been extensively applied to various cellular imaging applications due to the long-term photostability and the tunable narrow emission spectra with broad excitation. Despite the great success of various bioimaging and diagnostic applications, visualization of intracellular targets in live cells still has been of great challenge. Nonspecific binding, difficulty of intracellular delivery, or endosomal trapping of nanosized QDs are the main reasons to hamper specific target binding in live cells. In this context, we prepared the polymer-coated QDs (pcQD) of which the surface was optimized for specific intracellular targeting in live cells. Efficient intracellular delivery was achieved through PEGylation and subsequent cell penetrating peptide (i.e., TAT) conjugation to the pcQD in order to avoid significant endosomal sequestration and to facilitate internalization of the QDs, respectively. In this study, we employed HEK293 cell line overexpressing endothelin A receptor (ET(A)R), a family of G-protein coupled receptor (GPCR), of which the cytosolic c-terminal site is genetically engineered to possess green fluorescent protein (GFP) as our intracellular protein target. The fluorescence signal of the target protein and the well-defined intracellular behavior of the GPCR help to evaluate the targeting specificity of QDs in living cells. To test the hypothesis that the TAT-QDs conjugated with antibody against intracellular target of interest can find the target, we conjugated anti-GFP antibody to TAT-PEG-pcQD using heterobifunctional linkers. Compared to the TAT-PEG-pcQD, which was distributed throughout the cytoplasm, the antiGFP-functionalized TAT-PEG-pcQD could penetrate the cell membrane and colocalize with the GFP. An agonist (endothelin-1, ET-1) treatment induced GFP-ET(A)R translocation into pericentriolar region, where the GFP also significantly colocalized with antiGFP-TAT-PEG-pcQD. These results demonstrate that stepwise optimization of PEG-pcQD conjugation with both a cell penetrating peptide and an antibody against a target of interest allows specific binding to the intracellular target protein with minimized nonspecific binding.

CXCL10 Is an Agonist of the CC Family Chemokine Scavenger Receptor ACKR2/D6.

Atypical chemokine receptors (ACKRs) are important regulators of chemokine functions. Among them, the atypical chemokine receptor ACKR2 (also known as D6) has long been considered as a scavenger of inflammatory chemokines exclusively from the CC family. In this study, by using highly sensitive ß-arrestin recruitment assays based on NanoBiT and NanoBRET technologies, we identified the inflammatory CXC chemokine CXCL10 as a new strong agonist ligand for ACKR2. CXCL10 is known to play an important role in the infiltration of immune cells into the tumour bed and was previously reported to bind to CXCR3 only. We demonstrated that ACKR2 is able to internalize and reduce the availability of CXCL10 in the extracellular space. Moreover, we found that, in contrast to CC chemokines, CXCL10 activity towards ACKR2 was drastically reduced by the dipeptidyl peptidase 4 (DPP4 or CD26) N-terminal processing, pointing to a different receptor binding pocket occupancy by CC and CXC chemokines. Overall, our study sheds new light on the complexity of the chemokine network and the potential role of CXCL10 regulation by ACKR2 in many physiological and pathological processes, including tumour immunology. Our data also testify that systematic reassessment of chemokine-receptor pairing is critically needed as important interactions may remain unexplored.

Gene-corrected p.A30P SNCA patient-derived isogenic neurons rescue neuronal branching and function.

Parkinson's disease (PD) is characterised by the degeneration of A9 dopaminergic neurons and the pathological accumulation of alpha-synuclein. The p.A30P SNCA mutation generates the pathogenic form of the alpha-synuclein protein causing an autosomal-dominant form of PD. There are limited studies assessing pathogenic SNCA mutations in patient-derived isogenic cell models. Here we provide a functional assessment of dopaminergic neurons derived from a patient harbouring the p.A30P SNCA mutation. Using two clonal gene-corrected isogenic cell lines we identified image-based phenotypes showing impaired neuritic processes. The pathological neurons displayed impaired neuronal activity, reduced mitochondrial respiration, an energy deficit, vulnerability to rotenone, and transcriptional alterations in lipid metabolism. Our data describes for the first time the mutation-only effect of the p.A30P SNCA mutation on neuronal function, supporting the use of isogenic cell lines in identifying image-based pathological phenotypes that can serve as an entry point for future disease-modifying compound screenings and drug discovery strategies.

Integrated, automated maintenance, expansion and differentiation of 2D and 3D patient-derived cellular models for high throughput drug screening.

Patient-derived cellular models become an increasingly powerful tool to model human diseases for precision medicine approaches. The identification of robust cellular disease phenotypes in these models paved the way towards high throughput screenings (HTS) including the implementation of laboratory advanced automation. However, maintenance and expansion of cells for HTS remains largely manual work. Here, we describe an integrated, complex automated platform for HTS in a translational research setting also designed for maintenance and expansion of different cell types. The comprehensive design allows automation of all cultivation steps and is flexible for development of methods for variable cell types. We demonstrate protocols for controlled cell seeding, splitting and expansion of human fibroblasts, induced pluripotent stem cells (iPSC), and neural progenitor cells (NPC) that allow for subsequent differentiation into different cell types and image-based multiparametric screening. Furthermore, we provide automated protocols for neuronal differentiation of NPC in 2D culture and 3D midbrain organoids for HTS. The flexibility of this multitask platform makes it an ideal solution for translational research settings involving experiments on different patient-derived cellular models for precision medicine.