Detection of Pancreatic Ductal Adenocarcinoma-Associated Proteins in Serum.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types, partly because it is frequently identified at an advanced stage, when surgery is no longer feasible. Therefore, early detection using minimally invasive methods such as blood tests may improve outcomes. However, studies to discover molecular signatures for the early detection of PDAC using blood tests have only been marginally successful. In the current study, a quantitative glycoproteomic approach via data-independent acquisition mass spectrometry was utilized to detect glycoproteins in 29 patient-matched PDAC tissues and sera. A total of 892 N-linked glycopeptides originating from 141 glycoproteins had PDAC-associated changes beyond normal variation. We further evaluated the specificity of these serum-detectable glycoproteins by comparing their abundance in 53 independent PDAC patient sera and 65 cancer-free controls. The PDAC tissue-associated glycoproteins we have identified represent an inventory of serum-detectable PDAC-associated glycoproteins as candidate biomarkers that can be potentially used for the detection of PDAC using blood tests.

Gate-tunable Intrinsic Anomalous Hall Effect in Epitaxial MnBi2Te4 Films.

The anomalous Hall effect (AHE) is an important transport signature revealing topological properties of magnetic materials and their spin textures. Recently, MnBi2Te4 has been demonstrated to be an intrinsic magnetic topological insulator. However, the origin of its intriguing AHE behaviors remains elusive. Here, we demonstrate the Berry curvature-dominated intrinsic AHE in wafer-scale MnBi2Te4 films. By applying back-gate voltages, we observe an ambipolar conduction and n-p transition in ∼7-layer MnBi2Te4, where a quadratic relation between the AHE resistance and longitudinal resistance suggests its intrinsic AHE nature. In particular, for ∼3-layer MnBi2Te4, the AHE sign can be tuned from pristine negative to positive. First-principles calculations unveil that such an AHE reversal originated from the competing Berry curvature between oppositely polarized spin-minority-dominated surface states and spin-majority-dominated inner bands. Our results shed light on the underlying physical mechanism of the intrinsic AHE and provide new perspectives for the unconventional sign-tunable AHE.

TiO2-modified MoS2 monolayer films enable sensitive NH3 sensing at room temperature.

The research and development of high-performance NH3 sensors are of great significance for environment monitoring and disease diagnosis applications. Two-dimensional (2D) MoS2 nanomaterials have exhibited great potential for building room-temperature (RT) NH3 sensors but still suffer from relatively low sensitivity. Herein, the TiO2-modified monolayer MoS2 films with controllable TiO2 loading contents are fabricated by a facile approach. A remarkable enhancement in the RT NH3 sensing performance is achieved after the n-n hetero-compositing of the TiO2/MoS2 system. The device with 95% surface coverage of TiO2 shows enhanced sensor response, low detection limit (0.5 ppm), wide detection range (0.5-1000 ppm), good repeatability, and superior selectivity against other gases. In situ Kelvin potential force microscopy results revealed that the TiO2 modification not only improved the surface reactivity of the sensing layers but also contributed to the NH3 sensing performance by serving as the "gas-gating" layers that modulated the electron depletion layer and the conductivity of the MoS2 films. Such an n-n hetero-compositing strategy can provide a simple and cost-effective approach for developing high-performance NH3 sensors based on 2D semiconductors.

Muscone promotes functional recovery by facilitating microglia polarization into M2 phenotype through PPAR-γ pathway after ischemic stroke.

Exploring regimens to facilitate microglia transformation from M1 to M2 phenotype is a feasible strategy to suppress neuroinflammation, therefore reinforcing functional recovery after ischemic stroke. Muscone easily crosses the blood brain barrier (BBB) and distributes throughout the brain. Here, the results illustrated the administration of 8 mg/kg muscone promoted functional recovery through reducing the infarct volume by 2,3,5-triphenyltetrazolium chloride (TTC) staining after ischemic stroke in mice. Then, the expression of pro-inflammatory factors, such as tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß) and interleukin-6 (IL-6), was significantly decreased, whereas the level of anti-inflammatory agents including C-X-C Motif Chemokine Ligand 1 (CXCL1), transforming growth factor-ß (TGF-ß) and interleukin-10 (IL-10) was obviously elevated in penumbra with the treatment of 8 mg/kg muscone using real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), western blot and enzyme-linked immunosorbent assay (ELISA) tests. Subsequently, the results showed the application of muscone upregulated the expression of peroxisome proliferator-activated receptor-γ (PPAR-γ) to facilitate microglia transformation into M2 phenotype using RT-qPCR, western blot and immunofluorescence analysis. Collectively, the present study provides evidence for our hypothesis that muscone intensifies microglia transformation into M2 phenotype via activating PPAR-γ signaling pathway in penumbra after ischemic stroke. These findings demonstrate muscone is a promising candidate for the treatment of ischemic stroke.

Cactus-Inspired Photonic Crystal Chip for Attomolar Fluorescence Multi-analysis.

Automation and efficiency requirements of environmental monitoring are the pursuit of spontaneous sampling and ultrasensitivity for current sensory systems or detection apparatuses. In this work, inspired by cactus hierarchical structures, we develop a cactus-inspired photonic crystal chip to integrate spontaneous droplet sampling and fluorescence enhancement for sensitive multi-analyte detection. A conical hydrophilic pattern on hydrophobic surfaces can give rise to unidirectional Laplace pressure, which drives droplet transport to the assigned photonic crystal site. The nanostructure of photonic crystals has bigger capillarity to drive the droplet wetting uniformly into the photonic crystal matrix while performing prominent fluorescence enhancement by their photonic bandgap. A low to attomolar (2.24 × 10-19 M) fluorescence limit of detection (LOD) sensitivity can be achieved by the synergy of spontaneous droplet sampling and fluorescence enhancement. Focused on eutrophic water problems and algae pollution monitoring, a femtomolar (1.83 × 10-15 M) LOD and identification of various microcystins in urban environmental water can be achieved. The suitable integration of the unidirectional droplet transport by Laplace pressure and fluorescence enhancement by photonic crystals can achieve the spontaneous sampling and signal enhancement for ultratrace detections and sample survey of environmental monitoring and disease diagnosis.

Understanding the complexity of existing fossil fuel power plant decarbonization.

Growing national decarbonization commitments require rapid and deep reductions of carbon dioxide emissions from existing fossil-fuel power plants. Although retrofitting existing plants with carbon capture and storage or biomass has been discussed extensively, yet such options have failed to provide evident emission reductions at a global scale so far. Assessments of decarbonization technologies tend to focus on one specific option but omit its interactions with competing technologies and related sectors (e.g., water, food, and land use). Energy system models could mimic such inter-technological and inter-sectoral competition but often aggregate plant-level parameters without validation, as well as fleet-level inputs with large variability and uncertainty. To enhance the accuracy and reliability of top-down optimization models, bottom-up plant-level experience accumulation is of vital importance. Identifying sweet spots for plant-level pilot projects, overcoming the technical, financial, and social obstacles of early large-scale demonstration projects, incorporating equity into the transition, propagating the plant-level potential to generate fleet-level impacts represent some key complexity of existing fossil-fuel power plant decarbonization challenges that imposes the need for a serious re-evaluation of existing fossil fuel power plant abatement in energy transition.

Characterization of core fucosylation via sequential enzymatic treatments of intact glycopeptides and mass spectrometry analysis.

Core fucosylation of N-linked glycoproteins has been linked to the functions of glycoproteins in physiological and pathological processes. However, quantitative characterization of core fucosylation remains challenging due to the complexity and heterogeneity of N-linked glycosylation. Here we report a mass spectrometry-based method that employs sequential treatment of intact glycopeptides with enzymes (STAGE) to analyze site-specific core fucosylation of glycoproteins. The STAGE method utilizes Endo F3 followed by PNGase F treatment to generate mass signatures for glycosites that are formerly modified by core fucosylated N-linked glycans. We benchmark the STAGE method and use it to characterize site specific core fucosylation of glycoproteins from human hepatocellular carcinoma and pancreatic ductal adenocarcinoma, resulting in the identification of 1130 and 782 core fucosylated glycosites, respectively. These results indicate that our STAGE method enables quantitative characterization of core fucosylation events from complex protein mixtures, which may benefit our understanding of core fucosylation functions in various diseases.

Optimized data-independent acquisition approach for proteomic analysis at single-cell level.

BACKGROUND: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

From Platform to Knowledge Graph: Evolution of Laboratory Automation.

High-fidelity computer-aided experimentation is becoming more accessible with the development of computing power and artificial intelligence tools. The advancement of experimental hardware also empowers researchers to reach a level of accuracy that was not possible in the past. Marching toward the next generation of self-driving laboratories, the orchestration of both resources lies at the focal point of autonomous discovery in chemical science. To achieve such a goal, algorithmically accessible data representations and standardized communication protocols are indispensable. In this perspective, we recategorize the recently introduced approach based on Materials Acceleration Platforms into five functional components and discuss recent case studies that focus on the data representation and exchange scheme between different components. Emerging technologies for interoperable data representation and multi-agent systems are also discussed with their recent applications in chemical automation. We hypothesize that knowledge graph technology, orchestrating semantic web technologies and multi-agent systems, will be the driving force to bring data to knowledge, evolving our way of automating the laboratory.

Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Signal peptide of HIV-1 envelope modulates glycosylation impacting exposure of V1V2 and other epitopes.

HIV-1 envelope (Env) is a trimer of gp120-gp41 heterodimers, synthesized from a precursor gp160 that contains an ER-targeting signal peptide (SP) at its amino-terminus. Each trimer is swathed by ~90 N-linked glycans, comprising complex-type and oligomannose-type glycans, which play an important role in determining virus sensitivity to neutralizing antibodies. We previously examined the effects of single point SP mutations on Env properties and functions. Here, we aimed to understand the impact of the SP diversity on glycosylation of virus-derived Env and virus neutralization by swapping SPs. Analyses of site-specific glycans revealed that SP swapping altered Env glycan content and occupancy on multiple N-linked glycosites, including conserved N156 and N160 glycans in the V1V2 region at the Env trimer apex and N88 at the trimer base. Virus neutralization was also affected, especially by antibodies against V1V2, V3, and gp41. Likewise, SP swaps affected the recognition of soluble and cell-associated Env by antibodies targeting distinct V1V2 configurations, V3 crown, and gp41 epitopes. These data highlight the contribution of SP sequence diversity in shaping the Env glycan content and its impact on the configuration and accessibility of V1V2 and other Env epitopes.

Proteomic signatures of 16 major types of human cancer reveal universal and cancer-type-specific proteins for the identification of potential therapeutic targets.

BACKGROUND: Proteomic characterization of cancers is essential for a comprehensive understanding of key molecular aberrations. However, proteomic profiling of a large cohort of cancer tissues is often limited by the conventional approaches. METHODS: We present a proteomic landscape of 16 major types of human cancer, based on the analysis of 126 treatment-naïve primary tumor tissues, 94 tumor-matched normal adjacent tissues, and 12 normal tissues, using mass spectrometry-based data-independent acquisition approach. RESULTS: In our study, a total of 8527 proteins were mapped to brain, head and neck, breast, lung (both small cell and non-small cell lung cancers), esophagus, stomach, pancreas, liver, colon, kidney, bladder, prostate, uterus and ovary cancers, including 2458 tissue-enriched proteins. Our DIA-based proteomic approach has characterized major human cancers and identified universally expressed proteins as well as tissue-type-specific and cancer-type-specific proteins. In addition, 1139 therapeutic targetable proteins and 21 cancer/testis (CT) antigens were observed. CONCLUSIONS: Our discoveries not only advance our understanding of human cancers, but also have implications for the design of future large-scale cancer proteomic studies to assist the development of diagnostic and/or therapeutic targets in multiple cancers.

In silico rationalisation of selectivity and reactivity in Pd-catalysed C-H activation reactions.

A computational approach has been developed to automatically generate and analyse the structures of the intermediates of palladium-catalysed carbon-hydrogen (C-H) activation reactions as well as to predict the final products. Implemented as a high-performance computing cluster tool, it has been shown to correctly choose the mechanism and rationalise regioselectivity of chosen examples from open literature reports. The developed methodology is capable of predicting reactivity of various substrates by differentiation between two major mechanisms - proton abstraction and electrophilic aromatic substitution. An attempt has been made to predict new C-H activation reactions. This methodology can also be used for the automated reaction planning, as well as a starting point for microkinetic modelling.

Human Influenza Virus Hemagglutinins Contain Conserved Oligomannose N-Linked Glycans Allowing Potent Neutralization by Lectins.

Hemagglutinins (HAs) from human influenza viruses adapt to bind α2-6-linked sialosides, overcoming a receptor-defined species barrier distinct from the α2-3 specificity of avian virus progenitors. Additionally, human-adapted HAs gain glycosylation sites over time, although their biological function is poorly defined. Using quantitative glycomic analysis, we show that HAs from human pandemic viruses exhibit significant proportions of high-mannose type N-linked glycans throughout the head domain. By contrast, poorly adapted avian-origin HAs contain predominately complex-type glycans, which have greater structural diversity. Although oligomannose levels vary, they are present in all tested recombinant HAs and whole viruses and can be specifically targeted for universal detection. The positions of high-mannose glycosites on the HA of human H1N1 and H3N2 strains are conserved. Additionally, high-mannose-binding lectins possess a broad capacity to neutralize and prevent infection with contemporary H3N2 strains. These findings reveal the biological significance of HA glycosylation and therapeutic potential of targeting these structures.

Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis.

Rational solvent selection remains a significant challenge in process development. Here we describe a hybrid mechanistic-machine learning approach, geared towards automated process development workflow. A library of 459 solvents was used, for which 12 conventional molecular descriptors, two reaction-specific descriptors, and additional descriptors based on screening charge density, were calculated. Gaussian process surrogate models were trained on experimental data from a Rh(CO)2(acac)/Josiphos catalysed asymmetric hydrogenation of a chiral α-ß unsaturated γ-lactam. With two simultaneous objectives - high conversion and high diastereomeric excess - the multi-objective algorithm, trained on the initial dataset of 25 solvents, has identified solvents leading to better reaction outcomes. In addition to being a powerful design of experiments (DoE) methodology, the resulting Gaussian process surrogate model for conversion is, in statistical terms, predictive, with a cross-validation correlation coefficient of 0.84. After identifying promising solvents, the composition of solvent mixtures and optimal reaction temperature were found using a black-box Bayesian optimisation. We then demonstrated the application of a new genetic programming approach to select an appropriate machine learning model for a specific physical system, which should allow the transition of the overall process development workflow into the future robotic laboratories.

Chromatographic determination and in-situ cell imaging of thiol compounds based on a fluorigenic probe.

This study combines a high-performance liquid chromatography-fluorescent detection method (HPLC-FLD) with in-situ cell imaging for the sensitive analysis of glutathione (GSH), cysteine (Cys) and homocysteine (Hcys), using BODIPY®507/545 IA as a labeling reagent. The analytical potential of BODIPY®507/545 IA in cell imaging was deeply explored, concerning fluorescent response, selectivity, cell-permeability, biotoxicity and so on. It is demonstrated that BODIPY®507/545 IA has good biocompatibility and the fluorescence intensity is enhanced remarkably after reacting with thiols. The best derivative condition was obtained in boric acid buffer (0.05 mmol/L, pH 9.5) at 45 °C for 15 min. For chromatographic method, two sensitive methods, HPLC-FLD and capillary electrophoresis-laser-induced fluorescence detection (CE-LIF) were both developed, validated, and compared. The detection limits for the thiols ranged from 5 to 10 nmol/L with HPLC-FLD and 0.5 nmol/L for the CE-LIF method. Finally, HPLC-FLD is adopted to quantify the thiols in HepG2 cell samples after cell imaging.

Differential processing of HIV envelope glycans on the virus and soluble recombinant trimer.

As the sole target of broadly neutralizing antibodies (bnAbs) to HIV, the envelope glycoprotein (Env) trimer is the focus of vaccination strategies designed to elicit protective bnAbs in humans. Because HIV Env is densely glycosylated with 75-90 N-glycans per trimer, most bnAbs use or accommodate them in their binding epitope, making the glycosylation of recombinant Env a key aspect of HIV vaccine design. Upon analysis of three HIV strains, we here find that site-specific glycosylation of Env from infectious virus closely matches Envs from corresponding recombinant membrane-bound trimers. However, viral Envs differ significantly from recombinant soluble, cleaved (SOSIP) Env trimers, strongly impacting antigenicity. These results provide a benchmark for virus Env glycosylation needed for the design of soluble Env trimers as part of an overall HIV vaccine strategy.