Mass spectrometry and protein analysis

Analysis of the fluorescent properties of vaginal fluid upon ageing

Detection and identification of body fluids are crucial aspects of forensic investigations, aiding in crime scene reconstructions and providing important leads. Although many methods have been developed for these purposes, no method is currently in use in the forensic field that allows rapid, non-contact detection and identification of vaginal fluids directly at the crime scene. The development of such technique is mainly challenged by the complex chemistry of the constituents, which can differ between donors and exhibits changes based on woman's menstrual cycle. The use of fluorescence spectroscopy has shown promise in this area for other biological fluids. Therefore, the aim of this study was to identify specific fluorescent signatures of vaginal fluid with fluorescence spectroscopy to allow on-site identification. Additionally, the fluorescent properties were monitored over time to gain insight in the temporal changes of the fluorescent spectra of vaginal fluid. The samples were excited at wavelengths ranging from 200 to 600 nm and the induced fluorescence emission was measured from 220 to 700 nm. Excitation and emission maps (EEMs) were constructed for eight donors at seven time points after donation. Four distinctive fluorescence peaks could be identified in the EEMs, indicating the presence of proteins, fluorescent oxidation products (FOX), and an unidentified component as the dominant contributors to the fluorescence. To further asses the fluorescence characteristics of vaginal fluid, the fluorescent signatures of protein and FOX were used to monitor protein and lipid oxidation reactions over time. The results of this study provide insights into the intrinsic fluorescent properties of vaginal fluid over time which could be used for the development of a detection and identification method for vaginal fluids. Furthermore, the observed changes in fluorescence signatures over time could be utilized to establish an accurate ageing model.

Data augmentation using continuous conditional generative adversarial networks for regression and its application to improved spectral sensing

Machine learning-assisted spectroscopy analysis faces a prominent constraint in the form of insufficient spectral samples, which hinders its effectiveness. Meanwhile, there is a lack of effective algorithms to simulate synthetic spectra from limited samples of real spectra for regression models in continuous scenarios. In this study, we introduced a continuous conditional generative adversarial network (CcGAN) to autonomously generate synthetic spectra. The labels employed for generating the spectral data can be arbitrarily selected from within the range of labels associated with the real spectral data. Our approach effectively produced spectra using a small spectral dataset obtained from a self-interference microring resonator (SIMRR)-based sensor. The generated synthetic spectra were subjected to evaluation using principal component analysis, revealing an inability to discern them from the real spectra. Finally, to enhance the DNN regression model, these synthetic spectra are incorporated into the original training dataset as an augmentation technique. The results demonstrate that the synthetic spectra generated by CcGAN exhibit exceptional quality and significantly enhance the predictive performance of the DNN model. In conclusion, CcGAN exhibits promising potential in generating high-quality synthetic spectra and delivers a superior data augmentation effect for regression tasks.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

A human identification system for hair shaft using RNA polymorphism

Hair is one of the common pieces of evidence at crime scenes, with abundant mitochondrial DNA but limited nuclear DNA in its shaft. It also helps to narrow the investigation scope to maternal lineage but fails to provide unique individual information. We assumed that RNA in hair shafts would be an alternative resource used to perform human identification based on the facts that (1) RNA retains the polymorphic information; (2) the multi-copy of RNA in a cell resists degradation as compared to the one-copy of nuclear DNA. In this study, we explored the potential of RNA polymorphism in hair shafts for forensic individual identification. A SNaPshot typing system was constructed using 18 SNPs located on 11 genes (ABCA13, AHNAK, EXPH5, KMT2D, KRT35, PPP1R15A, RBM33, S100A5, TBC1D4, TMC5, TRPV2). The RNA typing system was evaluated for sensitivity, species specificity, and feasibility for aged hair samples. Hair samples from a Shanxi population in China were used for the population study of the system. The detection limit of the assay was 2 ng RNA. The CDP of these 11 genes was 0.999969 in the Shanxi population. We also identified the concordance of the RNA and DNA typing results. In summary, we developed an RNA typing method to perform human identification from hair shafts, which performed as accurately as nuclear DNA typing. Our method provides a potential basis for solving the human identification problem from hair shafts, as well as other biological materials that lack nuclear DNA.

Unveiling the Molecular Footprint: Proteome-Based Biomarkers for Alzheimer's Disease

Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Early and accurate diagnosis of AD is crucial for implementing timely interventions and developing effective therapeutic strategies. Proteome-based biomarkers have emerged as promising tools for AD diagnosis and prognosis due to their ability to reflect disease-specific molecular alterations. There is of great significance for biomarkers in AD diagnosis and management. It emphasizes the limitations of existing diagnostic approaches and the need for reliable and accessible biomarkers. Proteomics, a field that comprehensively analyzes the entire protein complement of cells, tissues, or bio fluids, is presented as a powerful tool for identifying AD biomarkers. There is a diverse range of proteomic approaches employed in AD research, including mass spectrometry, two-dimensional gel electrophoresis, and protein microarrays. The challenges associated with identifying reliable biomarkers, such as sample heterogeneity and the dynamic nature of the disease. There are well-known proteins implicated in AD pathogenesis, such as amyloid-beta peptides, tau protein, Apo lipoprotein E, and clusterin, as well as inflammatory markers and complement proteins. Validation and clinical utility of proteome-based biomarkers are addressing the challenges involved in validation studies and the diagnostic accuracy of these biomarkers. There is great potential in monitoring disease progression and response to treatment, thereby aiding in personalized medicine approaches for AD patients. There is a great role for bioinformatics and data analysis in proteomics for AD biomarker research and the importance of data preprocessing, statistical analysis, pathway analysis, and integration of multi-omics data for a comprehensive understanding of AD pathophysiology. In conclusion, proteome-based biomarkers hold great promise in the field of AD research. They provide valuable insights into disease mechanisms, aid in early diagnosis, and facilitate personalized treatment strategies. However, further research and validation studies are necessary to harness the full potential of proteome-based biomarkers in clinical practice.

Early Pregnancy Markers in the Serum of Ewes Identified via Proteomic and Metabolomic Analyses

The diagnosis of ewes' pregnancy status at an early stage is an efficient way to enhance the reproductive output of sheep and allow producers to optimize production and management. The techniques of proteomics and metabolomics have been widely used to detect regulatory factors in various physiological processes of animals. The aim of this study is to explore the differential metabolites and proteins in the serum of pregnant and non-pregnant ewes by proteomics and metabolomics. The serum of ewes at 21, 28 and 33 days after artificial insemination (AI) were collected. The pregnancy stratus of the ewes was finally determined through ultrasound examination and then the ewes were grouped as Pregnant (n = 21) or N on-pregnant (n = 9). First, the serum samples from pregnant or non-pregnant ewes at 21 days after AI were selected for metabolomic analysis. It was found that the level of nine metabolites were upregulated and 20 metabolites were downregulated in the pregnant animals (p < 0.05). None of these differential metabolomes are suitable as markers of pregnancy due to their small foldchange. Next, the proteomes of serum from pregnant or non-pregnant ewes were evaluated. At 21 days after AI, the presence of 321 proteins were detected, and we found that the level of three proteins were upregulated and 11 proteins were downregulated in the serum of pregnant ewes (p < 0.05). The levels of serum amyloid A (SAA), afamin (AFM), serpin family A member 6 (SERPINA6) and immunoglobulin-like domain-containing protein between pregnant and non-pregnant ewes at 21-, 28- and 33-days post-AI were also analyzed via enzyme-linked immunosorbent assay (ELISA). The levels of SAA and AFM were significantly higher in pregnant ewes than in non-pregnant ewes, and could be used as markers for early pregnancy detection. Overall, our results show that SAA and AFM are potential biomarkers to determine the early pregnancy status of ewes.

Analysis of histidine-tagged recombinant proteins from nickel and copper coated surfaces by direct electrospray ionization and desorption electrospray ionization mass spectrometry

RATIONALE

Purification of recombinant proteins is a necessary step for functional or structural studies and other applications. Immobilized metal affinity chromatography is a common recombinant protein purification method. Mass spectrometry (MS) allows for confirmation of identity of expressed proteins and unambiguous detection of enzymatic substrates and reaction products. We demonstrate the detection of enzymes purified on immobilized metal affinity surfaces by direct or ambient ionization MS, and follow their enzymatic reactions by direct electrospray ionization (ESI) or desorption electrospray ionization (DESI).

METHODS

A protein standard, His-Ubq, and two recombinant proteins, His-SHAN and His-CS, expressed in Escherichia coli were immobilized on two immobilized metal affinity systems, Cu-nitriloacetic acid (Cu-NTA) and Ni-NTA. The proteins were purified on surface, and released in the ESI spray solvent for direct infusion, when using the 96-well plate form factor, or analyzed directly from immobilized metal affinity-coated microscope slides by DESI-MS. Enzyme activity was followed by incubating the substrates in wells or by depositing substrate on immobilized protein on coated slides for analysis.

RESULTS

Small proteins (His-Ubq) and medium proteins (His-SAHN) could readily be detected from 96-well plates by direct infusion ESI, or from microscope slides by DESI-MS after purification on surface from clarified E. coli cell lysate. Protein oxidation was observed for immobilized proteins on both Cu-NTA and Ni-NTA; however, this did not hamper the enzymatic reactions of these proteins. Both the nucleosidase reaction products for His-SAHN and the methylation product of His-CS (theobromine to caffeine) were detected.

CONCLUSIONS

The immobilization, purification, release and detection of His-tagged recombinant proteins using immobilized metal affinity surfaces for direct infusion ESI-MS or ambient DESI-MS analyses were successfully demonstrated. Recombinant proteins were purified to allow identification directly out of clarified cell lysate. Biological activities of the recombinant proteins were preserved allowing the investigation of enzymatic activity via MS.

Advances in Ultrahigh Throughput Hit Discovery with Tandem Mass Spectrometry Encoded Libraries

Discovering new bioactive molecules is crucial for drug development. Finding a hit compound for a new drug target usually requires screening of millions of molecules. Affinity selection based technologies have revolutionized early hit discovery by enabling the rapid screening of libraries with millions or billions of compounds in short timeframes. In this Perspective, we describe recent technology breakthroughs that enable the screening of ultralarge synthetic peptidomimetic libraries with a barcode-free tandem mass spectrometry decoding strategy. A combination of combinatorial synthesis, affinity selection, automated de novo peptide sequencing algorithms, and advances in mass spectrometry instrumentation now enables hit discovery from synthetic libraries with over 100 million members. We provide a perspective on this powerful technology and showcase success stories featuring the discovery of high affinity binders for a number of drug targets including proteins, nucleic acids, and specific cell types. Further, we show the usage of the technology to discover synthetic peptidomimetics with specific functions and reactivity. We predict that affinity selection coupled with tandem mass spectrometry and automated de novo decoding will rapidly evolve further and become a broadly used drug discovery technology.

Improving quantitation accuracy in isobaric-labeling mass spectrometry experiments with spectral library searching and feature-based peptide-spectrum match filter

Isobaric labeling relative quantitation is one of the dominating proteomic quantitation technologies. Traditional quantitation pipelines for isobaric-labeled mass spectrometry data are based on sequence database searching. In this study, we present a novel quantitation pipeline that integrates sequence database searching, spectral library searching, and a feature-based peptide-spectrum-match (PSM) filter using various spectral features for filtering. The combined database and spectral library searching results in larger quantitation coverage, and the filter removes PSMs with larger quantitation errors, retaining those with higher quantitation accuracy. Quantitation results show that the proposed pipeline can improve the overall quantitation accuracy at the PSM and protein levels. To our knowledge, this is the first study that utilizes spectral library searching to improve isobaric labeling-based quantitation. For users to conveniently perform the proposed pipeline, we have implemented the feature-based filter being executable on both Windows and Linux platforms; its executable files, user manual, and sample data sets are freely available at https://ms.iis.sinica.edu.tw/comics/Software_FPF.html . Furthermore, with the developed filter, the proposed pipeline is fully compatible with the Trans-Proteomic Pipeline.

Investigation of targets and anticancer mechanisms of covalently acting natural products by functional proteomics

Eriocalyxin B (EB), 17-hydroxy-jolkinolide B (HJB), parthenolide (PN), xanthatin (XT) and andrographolide (AG) are terpenoid natural products with a variety of promising antitumor activities, which commonly bear electrophilic groups (α,β-unsaturated carbonyl groups and/or epoxides) capable of covalently modifying protein cysteine residues. However, their direct targets and underlying molecular mechanisms are still largely unclear, which limits the development of these compounds. In this study, we integrated activity-based protein profiling (ABPP) and quantitative proteomics approach to systematically characterize the covalent targets of these natural products and their involved cellular pathways. We first demonstrated the anti-proliferation activities of these five compounds in triple-negative breast cancer cell MDA-MB-231. Tandem mass tag (TMT)-based quantitative proteomics showed all five compounds commonly affected the ubiquitin mediated proteolysis pathways. ABPP platform identified the preferentially modified targets of EB and PN, two natural products with high anti-proliferation activity. Biochemical experiments showed that PN inhibited the cell proliferation through targeting ubiquitin carboxyl-terminal hydrolase 10 (USP10). Together, this study uncovered the covalently modified targets of these natural products and potential molecular mechanisms of their antitumor activities.

Extracellular Matrix Proteomics: The mdx-4cv Mouse Diaphragm as a Surrogate for Studying Myofibrosis in Dystrophinopathy

The progressive degeneration of the skeletal musculature in Duchenne muscular dystrophy is accompanied by reactive myofibrosis, fat substitution, and chronic inflammation. Fibrotic changes and reduced tissue elasticity correlate with the loss in motor function in this X-chromosomal disorder. Thus, although dystrophinopathies are due to primary abnormalities in the DMD gene causing the almost-complete absence of the cytoskeletal Dp427-M isoform of dystrophin in voluntary muscles, the excessive accumulation of extracellular matrix proteins presents a key histopathological hallmark of muscular dystrophy. Animal model research has been instrumental in the characterization of dystrophic muscles and has contributed to a better understanding of the complex pathogenesis of dystrophinopathies, the discovery of new disease biomarkers, and the testing of novel therapeutic strategies. In this article, we review how mass-spectrometry-based proteomics can be used to study changes in key components of the endomysium, perimysium, and epimysium, such as collagens, proteoglycans, matricellular proteins, and adhesion receptors. The mdx-4cv mouse diaphragm displays severe myofibrosis, making it an ideal model system for large-scale surveys of systematic alterations in the matrisome of dystrophic fibers. Novel biomarkers of myofibrosis can now be tested for their appropriateness in the preclinical and clinical setting as diagnostic, pharmacodynamic, prognostic, and/or therapeutic monitoring indicators.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Protein biomarkers for radiation injury and testing of medical countermeasure efficacy: promises, pitfalls, and future directions

INTRODUCTION

Radiological/nuclear accidents, hostile military activity, or terrorist strikes have the potential to expose a large number of civilians and military personnel to high doses of radiation resulting in the development of acute radiation syndrome and delayed effects of exposure. Thus, there is an urgent need for sensitive and specific assays to assess the levels of radiation exposure to individuals. Such radiation exposures are expected to alter primary cellular proteomic processes, resulting in multifaceted biological responses.

AREAS COVERED

This article covers the application of proteomics, a promising and fast developing technology based on quantitative and qualitative measurements of protein molecules for possible rapid measurement of radiation exposure levels. Recent advancements in high-resolution chromatography, mass spectrometry, high-throughput, and bioinformatics have resulted in comprehensive (relative quantitation) and precise (absolute quantitation) approaches for the discovery and accuracy of key protein biomarkers of radiation exposure. Such proteome biomarkers might prove useful for assessing radiation exposure levels as well as for extrapolating the pharmaceutical dose of countermeasures for humans based on efficacy data generated using animal models.

EXPERT OPINION

The field of proteomics promises to be a valuable asset in evaluating levels of radiation exposure and characterizing radiation injury biomarkers.

In vitro knockdown of TsDNase II-7 suppresses Trichinella spiralis invasion into the host's intestinal epithelial cells

Trichinella spiralis (T. spiralis) adult-specific deoxyribonuclease II-7 (TsDNase II-7), a member of the DNase II-like nuclease family with no DNase II activity, was identified in the excretory-secretory (ES) products of adult worms (AWs). However, its biological functions are still unclear. Our previous study revealed that TsDNase II-7 is located around the infection site in the intestinal tissue, speculating that it was involved in the T. spiralis invasion of host intestinal epithelial cells (IECs). This study aimed to use RNA interference to verify our speculation that TsDNase II-7 in 3-day old adult T. spiralis (Ad3) plays a role in intestinal invasion. TsDNase II-7-specific small interfering RNAs (siRNAs) were delivered into muscle larvae (MLs) to knockdown TsDNase II-7 expression by electroporation. Twenty-four hours later, the MLs transfected with 2 μM siRNA-841 exhibited decreased in TsDNase II-7 transcription and expression as compared to the control MLs. The knockdown of TsDNase II-7 expression did not affect ML viability, and the low expression of TsDNase II-7 still maintained in Ad3 recovered from TsDNase II-7-RNAi-ML infected mice, resulting in a weakened ability of Ad3 to invade intestinal epithelial cells (IECs). These results indicated that knockdown of TsDNase II-7 gene expression via RNA interference (RNAi) suppressed adult worm invasion and confirmed that TsDNase II-7 plays a crucial role during the intestinal phase of T. spiralis infections, which provided new candidate for vaccine development of T. spiralis.

Acoustically-Targeted Measurement of Transgene Expression in the Brain

Gene expression is a critical component of brain physiology and activity, but monitoring this expression in the living brain represents a significant challenge. Here, we introduce a new paradigm called Recovery of Markers through InSonation (REMIS) for noninvasive measurement of gene expression in the brain with cell-type, spatial, and temporal specificity. Our approach relies on engineered protein markers that are designed to be expressed in neurons and exit into the interstitium. By applying ultrasound to targeted brain regions, these markers are released into the bloodstream, where they can be readily detected using biochemical techniques. REMIS can noninvasively confirm gene delivery and measure endogenous signaling in specific brain sites through a simple insonation and a subsequent blood test. Using REMIS, we successfully measured chemogenetic induction of neuronal activity in ultrasound-tar-geted brain regions. REMIS recovery of markers is reliable and demonstrated improved recovery of markers from the brain into the blood in every tested animal. Overall, our work establishes a noninvasive, spatially-specific means of monitoring gene delivery outcomes and endogenous signaling in mammalian brains, opening up possibilities for brain research and noninvasive monitoring of gene therapies in the brain.

Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses

Proteomics research has been transformed due to high-throughput liquid chromatography (LC-MS/MS) tandem mass spectrometry instruments combined with highly sophisticated automated sample preparation and multiplexing workflows. However, scaling proteomics experiments to large sample cohorts (hundreds to thousands) requires thoughtful quality control (QC) protocols. Robust QC protocols can help with reproducibility, quantitative accuracy, and provide opportunities for more decisive troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of N = 335 patient samples using tandem mass tag (TMT_pro) 16-plex batches. Over the course of a 10-month data acquisition period for this cohort we collected 271 pooled QC LC-MS/MS result files obtained from MS/MS analysis of a patient-derived pooled plasma sample, representative of the entire cohort population. This sample was tagged with TMT_zero or TMT_pro reagents and used to inform the daily performance of the LC-MS/MS instruments and to allow within and across sample batch normalization. Analytical variability of a number of instrumental and data analysis metrics including protein and peptide identifications, peptide spectral matches (PSMs), number of obtained MS/MS spectra, average peptide abundance, percent of peptides with a Δ m/z between ±0.003 Da, percent of MS/MS spectra obtained at the maximum injection time, and the retention time of selected tracking peptides were evaluated to help inform the design of a robust LC-MS/MS QC workflow for use in future cohort studies. This study also led to general tips for using selected metrics to inform real-time troubleshooting of LC-MS/MS performance issues with daily QC checks.

ScerePhoSite: An interpretable method for identifying fungal phosphorylation sites in proteins using sequence-based features

Protein phosphorylation plays a vital role in signal transduction pathways and diverse cellular processes. To date, a tremendous number of in silico tools have been designed for phosphorylation site identification, but few of them are suitable for the identification of fungal phosphorylation sites. This largely hampers the functional investigation of fungal phosphorylation. In this paper, we present ScerePhoSite, a machine learning method for fungal phosphorylation site identification. The sequence fragments are represented by hybrid physicochemical features, and then LGB-based feature importance combined with the sequential forward search method is used to choose the optimal feature subset. As a result, ScerePhoSite surpasses current available tools and shown a more robust and balanced performance. Furthermore, the impact and contribution of specific features on the model performance were investigated by SHAP values. We expect ScerePhoSite to be a useful bioinformatics tool that complements hands-on experiments for the pre-screening of possible phosphorylation sites and facilitates our functional understanding of phosphorylation modification in fungi. The source code and datasets are accessible at https://github.com/wangchao-malab/ScerePhoSite/.

Protein Profiling in Human Papillomavirus-Associated Cervical Carcinogenesis: Cornulin as a Biomarker for Disease Progression

Nearly 90% of cervical cancers are linked to human papillomavirus (HPV). Uncovering the protein signatures in each histological phase of cervical oncogenesis provides a path to biomarker discovery. The proteomes extracted from formalin-fixed paraffin-embedded tissues of the normal cervix, HPV16/18-associated squamous intraepithelial lesion (SIL), and squamous cell carcinoma (SCC) were compared using liquid chromatography-mass spectrometry (LC-MS). A total of 3597 proteins were identified, with 589, 550, and 1570 proteins unique to the normal cervix, SIL, and SCC groups, respectively, while 332 proteins overlapped between the three groups. In the transition from normal cervix to SIL, all 39 differentially expressed proteins were downregulated, while all 51 proteins discovered were upregulated in SIL to SCC. The binding process was the top molecular function, while chromatin silencing in the SIL vs. normal group, and nucleosome assembly in SCC vs. SIL groups was the top biological process. The PI3 kinase pathway appears crucial in initiating neoplastic transformation, while viral carcinogenesis and necroptosis are important for cell proliferation, migration, and metastasis in cervical cancer development. Annexin A2 and cornulin were selected for validation based on LC-MS results. The former was downregulated in the SIL vs. normal cervix and upregulated in the progression from SIL to SCC. In contrast, cornulin exhibited the highest expression in the normal cervix and lowest in SCC. Although other proteins, such as histones, collagen, and vimentin, were differentially expressed, their ubiquitous expression in most cells precluded further analysis. Immunohistochemical analysis of tissue microarrays found no significant difference in Annexin A2 expression between the groups. Conversely, cornulin exhibited the strongest expression in the normal cervix and lowest in SCC, supporting its role as a tumor suppressor and potential biomarker for disease progression.

Analysis of differentially expressed proteins after EHP-infection and characterization of caspase 3 protein in the whiteleg shrimp (Litopenaeus vannamei)

Whiteleg shrimp (Litopenaeus vannamei) is the most important species of shrimp farmed worldwide in terms of its economic value. Enterocytozoon hepatopenaei (EHP) infects the hepatopancreas, resulting in the hepatopancreatic microsporidiosis (HPM) of the host, which causes slow growth of the shrimp and poses a threat to the farming industry. In this study, differentially expressed proteins (DEPs) between EHP-infected and uninfected shrimp were investigated through proteomics sequencing. A total of 9908 peptides and 2092 proteins were identified. A total of 69 DEPs were identified in the hepatopancreas (HP), of which, 28 were upregulated and 41 were downregulated. Our results showed that the differences among the level of multiple proteins involved in the apoptosis were significant after the EHP infection, which indicated that the apoptosis pathway was activated in whiteleg shrimp. In addition, expression leve of caspase 3 gene were identified related to the EHP infection. Furthermore, predictions of spatial structure, analysis of phylogeny and chromosome-level linearity of the caspase 3 protein were performed as well. In conclusion, a relatively complete proteomic data set of hepatopancreas tissues in whiteleg shrimp were established in this study. Findings about genes involved in the apoptosis here will provide a further understanding of the molecular mechanism of EHP infection in the internal immunity of whiteleg shrimp.

AMPK phosphorylates and stabilises copper transporter 1 to synergise metformin and copper chelator for breast cancer therapy

BACKGROUND

Predominant roles of copper and its transporter, copper transporter 1 (CTR1), in tumorigenesis have been explored recently; however, the upstream regulation of CTR1 and combinational intervention of copper chelators in malignancies remain largely unclear.

METHODS

CRISPR/Cas9-based kinome screening was used to identify the CTR1 upstream kinases. Immunofluorescence assays were utilised to detect CTR1 localisation. In vitro kinase assays and mass spectrometry were performed to detect CTR1 phosphorylation. Ubiquitination assays were performed to validate CTR1 stability. Colony formation, EdU labelling, Annexin V-FITC/PI-based apoptosis assays were carried out to detect the drug effect on cell growth and apoptosis. Xenografted mouse models were employed to investigate drug effects in vivo.

RESULTS

We identify that CTR1 undergoes AMPK-mediated phosphorylation, which enhances CTR1 stabilisation and membrane translocation by affecting Nedd4l interaction, resulting in increased oncogenic roles in breast cancer. Importantly, activation of AMPK with its agonist metformin markedly enhances CTR1 levels, and leads to the combinational usage of AMPK agonists and copper chelators for breast cancer treatment.

CONCLUSIONS

Our findings not only reveal the crosstalk between energy response and copper uptake via AMPK-mediated CTR1 phosphorylation and stability but also highlight the strategy to combat breast cancer by a combination of AMPK agonists and copper chelators.

SIGNIFICANCE

The connection between energy response and copper homoeostasis is linked by AMPK phosphorylating and stabilising CTR1, which provides a promising strategy to combat breast cancer by combining AMPK agonists and copper chelators.

A review of sensors for classification and subtype discrimination of cancer: Insights into circulating tumor cells and tumor-derived extracellular vesicles

Liquid biopsy can reflect the state of tumors in vivo non-invasively, thus providing a strong basis for the early diagnosis, individualized treatment monitoring and prognosis of tumors. Circulating tumor cells (CTCs) and tumor-derived extracellular vesicles (tdEVs) contain information-rich components, such as nucleic acids and proteins, and they are essential markers for liquid biopsies. Their capture and analysis are of great importance for the study of disease occurrence and development and, consequently, have been the subject of many reviews. However, both CTCs and tdEVs carry the biological characteristics of their original tissue, and few reviews have focused on their function in the staging and classification of cancer. In this review, we focus on state-of-the-art sensors based on the simultaneous detection of multiple biomarkers within CTCs and tdEVs, with clinical applications centered on cancer classification and subtyping. We also provide a thorough discussion of the current challenges and prospects for novel sensors with the ultimate goal of cancer classification and staging. It is hoped that these most advanced technologies will bring new insights into the clinical practice of cancer screening and diagnosis.

Prognostic circulating proteomic biomarkers in colorectal liver metastases

The liver is the most common site of metastasis in colorectal cancer. Multimodal treatment, including liver resection, is potentially curative and prolongs survival for selected patients with colorectal liver metastases (CRLM). However, the treatment of CRLM remains challenging because recurrence is common, and prognosis varies widely between patients despite curative-intent treatment. Clinicopathological features and tissue-based molecular biomarkers, either alone or in combination, are insufficient for accurate prognostication. As most of the functional information in cells resides in the proteome, circulating proteomic biomarkers may be useful for rationalising the molecular complexities of CRLM and identifying potentially prognostic molecular subtypes. High-throughput proteomics has accelerated a range of applications including protein profiling of liquid biopsies for biomarker discovery. Moreover, these proteomic biomarkers may provide non-invasive prognostic information even before CRLM resection. This review evaluates recently discovered circulating proteomic biomarkers in CRLM. We also highlight some of the challenges and opportunities with translating these discoveries into clinical applications.

Continuous Validation Across Macromolecular Structure Determination Process

The overall quality of the experimentally determined structures contained in the PDB is exceptionally high, mainly due to the continuous improvement of model building and structural validation programs. Improving reproducibility on a large scale requires expanding the concept of validation in structural biology and all other disciplines to include a broader framework that encompasses the entire project. A successful approach to science requires diligent attention to detail and a focus on the future. An earnest commitment to data availability and reuse is essential for scientific progress, be that by human minds or artificial intelligence.

Recent advances of small extracellular vesicle biomarkers in breast cancer diagnosis and prognosis

Current clinical tools for breast cancer (BC) diagnosis are insufficient but liquid biopsy of different bodily fluids has recently emerged as a minimally invasive strategy that provides a real-time snapshot of tumour biomarkers for early diagnosis, active surveillance of progression, and post-treatment recurrence. Extracellular vesicles (EVs) are nano-sized membranous structures 50-1000 nm in diameter that are released by cells into biological fluids. EVs contain proteins, nucleic acids, and lipids which play pivotal roles in tumourigenesis and metastasis through cell-to-cell communication. Proteins and miRNAs from small EVs (sEV), which range in size from 50-150 nm, are being investigated as a potential source for novel BC biomarkers using mass spectrometry-based proteomics and next-generation sequencing. This review covers recent developments in sEV isolation and single sEV analysis technologies and summarises the sEV protein and miRNA biomarkers identified for BC diagnosis, prognosis, and chemoresistance. The limitations of current sEV biomarker research are discussed along with future perspective applications.

Clinical application of serum-based proteomics technology in human tumor research

The rapid development of proteomics technology in the past decades has led to further human understanding of tumor research, and in some ways, the technology plays a very important supporting role in the early detection of tumors. Human serum has been shown to contain a variety of proteins closely related to life activities, and the dynamic change in proteins can often reflect the physiological and pathological conditions of the body. Serum has the advantage of easy extraction, so the application of proteomics technology in serum has become a hot spot and frontier area for the study of malignant tumors. However, there are still many difficulties in the standardized use of proteomic technologies, which inevitably limit the clinical application of proteomic technologies due to the heterogeneity of human proteins leading to incomplete whole proteome populations, in addition to most serum protein markers being now not highly specific in aiding the early detection of tumors. Nevertheless, further development of proteomics technologies will greatly increase our understanding of tumor biology and help discover more new tumor biomarkers with specificity that will enable medical technology.

Analysis of Isotopically Depleted Proteins Derived from Escherichia coli and Caenorhabditis elegans Cell Lines by Liquid Chromatography 21 T Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry

Protein mass measurement by mass spectrometry is complicated by wide isotopic distributions that result from incorporation of heavy isotopes of C, H, N, O, and S, thereby limiting signal-to-noise ratio (SNR) and accurate intact mass determination, particularly for larger proteins [Fenselau et al. Anal. Chem. 1983, 55 (2), 353-356]. Observation of the monoisotopic mass-to-charge ratio (m/z) is the simplest and most accurate way to determine intact protein mass, but as mass increases, the relative abundance of the monoisotopic peak becomes so low that it is often undetectable. Here, we used an isotopically depleted growth medium to culture bacterial cells (Escherichia coli), resulting in isotopically depleted proteins. Isotopically depleted proteins show increased sequence coverage, mass measurement accuracy, and increased S/N of the monoisotopic peak by Fourier transform ion cyclotron resonance mass spectrometry analysis. We then grew Caenorhabditis elegans cells in a medium containing living isotopically depleted E. coli cells, thereby producing the first isotopically depleted eukaryotic proteins. This is the first time isotopic depletion has been implemented for four isotopes (¹H, ¹²C, ¹⁴N, and ¹⁶O), resulting in the highest degree of depletion ever used for protein analysis and further improving MS analysis.

Advancement in COVID-19 detection using nanomaterial-based biosensors

Coronavirus disease 2019 (COVID-19) pandemic has exemplified how viral growth and transmission are a significant threat to global biosecurity. The early detection and treatment of viral infections is the top priority to prevent fresh waves and control the pandemic. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified through several conventional molecular methodologies that are time-consuming and require high-skill labor, apparatus, and biochemical reagents but have a low detection accuracy. These bottlenecks hamper conventional methods from resolving the COVID-19 emergency. However, interdisciplinary advances in nanomaterials and biotechnology, such as nanomaterials-based biosensors, have opened new avenues for rapid and ultrasensitive detection of pathogens in the field of healthcare. Many updated nanomaterials-based biosensors, namely electrochemical, field-effect transistor, plasmonic, and colorimetric biosensors, employ nucleic acid and antigen-antibody interactions for SARS-CoV-2 detection in a highly efficient, reliable, sensitive, and rapid manner. This systematic review summarizes the mechanisms and characteristics of nanomaterials-based biosensors for SARS-CoV-2 detection. Moreover, continuing challenges and emerging trends in biosensor development are also discussed.

Focus on the molecular mechanisms of cisplatin resistance based on multi-omics approaches

Cisplatin is commonly used in combination with other cytotoxic agents as a standard treatment regimen for a variety of solid tumors, such as lung, ovarian, testicular, and head and neck cancers. However, the effectiveness of cisplatin is accompanied by toxic side effects, for instance, nephrotoxicity and neurotoxicity. The response of tumors to cisplatin treatment involves multiple physiological processes, and the efficacy of chemotherapy is limited by the intrinsic and acquired resistance of tumor cells. Although enormous efforts have been made toward molecular mechanisms of cisplatin resistance, the development of omics provides new insights into the understanding of cisplatin resistance at genome, transcriptome, proteome, metabolome and epigenome levels. Mechanism studies using different omics approaches revealed the necessity of multi-omics applications, which provide information at different cellular function levels and expand our recognition of the peculiar genetic and phenotypic heterogeneity of cancer. The present work systematically describes the underlying mechanisms of cisplatin resistance in different tumor types using multi-omics approaches. In addition to the classical mechanisms such as enhanced drug efflux, increased DNA damage repair and changes in the cell cycle and apoptotic pathways, other changes like increased protein damage clearance, increased protein glycosylation, enhanced glycolytic process, dysregulation of the oxidative phosphorylation pathway, ferroptosis suppression and mRNA m6A methylation modification can also induce cisplatin resistance. Therefore, utilizing the integrated omics to identify key signaling pathways, target genes and biomarkers that regulate chemoresistance are essential for the development of new drugs or strategies to restore tumor sensitivity to cisplatin.

Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles

The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.

Online coupling of matrix solid-phase dispersion to direct analysis in real time mass spectrometry for high-throughput analysis of regulated chemicals in consumer products

The current work is the first study on online coupling of matrix solid-phase dispersion (MSPD) to direct analysis in real time mass spectrometry (DART-MS) bridging with solid-phase analytical derivatization (SPAD) based on a graphene oxide nanosheets (GONs)-coated cotton swab. Proof-of-concept demonstrations were explored for high-throughput analysis of a diversity of regulated chemicals in consumer products such as textiles, toys, and cosmetics. On-demand sorbent combinations were blended with samples, packed into MSPD columns, and mounted on a homemade 3D-printed rack module for automated sample feeding. To achieve good synergy between MSPD and DART-MS, a cotton swab with a conical tip deposited with GONs was attached to the bottom of the MSPD column. The swabs serve as a solid-phase microextraction probe for convenient enrichment of the eluted analytes from MSPD, thermal desorption of the enriched analytes by DART, and sensitive detection by a hybrid quadrupole-Orbitrap mass spectrometer. Furthermore, the utility of an on-swab SPAD strategy was demonstrated for the detection of formaldehyde by use of the derivatizing reagent of dansyl hydrazine, contributing to improved ionization efficiency without compromising the overall coherence of the analytical workflow. The MSPD-DART-MS methodology was systematically optimized and validated, obtaining acceptable recovery (71.7-110.3%), repeatability (11.8-19.3%), and sensitivity (limits of detection and quantitation in the ranges of 6.2-19.5 and 23.7-75.9 μg/kg) for 32 target analytes. The developed protocol streamlined sample extraction, clean-up, desorption, ionization, and detection, highlighting the appealing potential for high-throughput analysis of samples with complex matrices.

Functional Fiber Materials to Smart Fiber Devices

The development of fiber materials has accompanied the evolution of human civilization for centuries. Recent advances in materials science and chemistry offered fibers new applications with various functions, including energy harvesting, energy storing, displaying, health monitoring and treating, and computing. The unique one-dimensional shape of fiber devices endows them advantages to work as human-interfaced electronics due to the small size, lightweight, flexibility, and feasibility for integration into large-scale textile systems. In this review, we first present a discussion of the basics of fiber materials and the design principles of fiber devices, followed by a comprehensive analysis on recently developed fiber devices. Finally, we provide the current challenges facing this field and give an outlook on future research directions. With novel fiber devices and new applications continuing to be discovered after two decades of research, we envision that new fiber devices could have an important impact on our life in the near future.

Protein Acetylation Increased Risk of Fibrosis-Related Liver Cancer

Objective

The occurrence of liver fibrosis and fibrosis-related liver cancer is the reason for the increase in morbidity and mortality worldwide. Transforming growth factor-β2 (TGF-β2) is an important mediator of chronic liver fibrosis. This study aims to find the molecular mechanism that mediates HBV infection and induces TGF-β2 and verifies that CREB binding protein acetylation mediates HBV infection and induces TGF-β2 expression.

Methods

The acetylated proteins were extracted from HepG2-NTCP cells and HBV-infectedHepG2-NTCP cells. The acetylated proteins were screened by modification enrichment technology and database search. Protein annotation, motif analysis of modification sites, and protein function enrichment analysis of these proteins were performed to roughly clarify the location and function of these acetylated modification proteins in cells. Acylated proteins enriched in the TGF-β pathway were obtained by KEGG pathway enrichment analysis. The effect of the selected acetylated modification protein on the TGF-β pathway was verified by experiments, that is, the target protein gene was knocked out by siRNA, and the expression level of the TGF-β2 was detected by qRT-PCR.

Results

Proteins were extracted from HepG2-NTCP cells and HepG2-NTCP cells infected with HBV, and differential acetylation modification proteins were screened. The target protein CREB binding protein was screened by modification enrichment technology and database search. The aggregation analysis of TGF-β pathway showed that CREB binding protein was acetylated at amino acid positions 434 and 439, and enriched in the TGF-β signaling pathway. siRNA targeting CREB binding protein was transfected, and the expression of TGF-β2 in cells was detected by qRT-PCR and western blot, respectively. It was verified that HBV infection-inducedCREB-binding protein acetylation regulated the high expression of TGF-β2.

Conclusion

After HBV infection, CREBBP acetylation was up-regulated, which promoted the high expression of TGF-β2.

Applications of Mass Spectrometry in Dentistry

Mass Spectrometry (MS) is one of the fastest-developing methods in analytical instrumentation. As a highly sensitive, universal detector, it can identify known and unknown compounds, which can indeed be found in a minimal concentration. This review aims to highlight the significant milestones in MS applications in dentistry during recent decades. MS can be applied in three different fields of dentistry: (1) in research of dental materials and chemical agents, (2) in laboratory analysis of biospecimens, and (3) as a real-time diagnostic tool in service of oral surgery and pathology. MS applications on materials and agents may focus on numerous aspects, such as their clinical behavior, possible toxicity, or antimicrobial properties. MS is also a valuable, non-invasive tool for biomarkers' detection in saliva and has found great application in -omics technologies as it achieves efficient structure-finding in metabolites. As metabolites are located beyond the central dogma, this technique can provide a complete understanding of cellular functions. Thus, it is possible to determine the biological profile in normal and pathological conditions, detect various oral or systematic diseases and conditions, and predict their course. Lastly, some promising advances concerning the surgical approach to potentially oral malignant or malignant disorders exist. This breakthrough method provides a comprehensive approach to dental materials research and biomarker discovery in dental and craniofacial tissues. The current availability of various 'OMIC' approaches paves the way for individualized dentistry and provides suggestions for clinical applications in the point-of-care hubs.

Protein content of blood-derived extracellular vesicles: An approach to the pathophysiology of cerebral hemorrhage

Introduction: Extracellular vesicles (EVs) participate in cell-to-cell paracrine signaling and can be biomarkers of the pathophysiological processes underlying disease. In intracerebral hemorrhage, the study of the number and molecular content of circulating EVs may help elucidate the biological mechanisms involved in damage and repair, contributing valuable information to the identification of new therapeutic targets. Methods: The objective of this study was to describe the number and protein content of blood-derived EVs following an intracerebral hemorrhage (ICH). For this purpose, an experimental ICH was induced in the striatum of Sprague-Dawley rats and EVs were isolated and characterized from blood at baseline, 24 h and 28 days. The protein content in the EVs was analyzed by mass spectrometric data-dependent acquisition; protein quantification was obtained by sequential window acquisition of all theoretical mass spectra data and compared at pre-defined time points. Results: Although no differences were found in the number of EVs, the proteomic study revealed that proteins related to the response to cellular damage such as deubiquitination, regulation of MAP kinase activity (UCHL1) and signal transduction (NDGR3), were up-expressed at 24 h compared to baseline; and that at 28 days, the protein expression profile was characterized by a higher content of the proteins involved in healing and repair processes such as cytoskeleton organization and response to growth factors (COR1B) and the regulation of autophagy (PI42B). Discussion: The protein content of circulating EVs at different time points following an ICH may reflect evolutionary changes in the pathophysiology of the disease.

The Need for Biomarkers in the ALS-FTD Spectrum: A Clinical Point of View on the Role of Proteomics

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are severely debilitating and progressive neurodegenerative disorders. A distinctive pathological feature of several neurodegenerative diseases, including ALS and FTD, is the deposition of aberrant protein inclusions in neuronal cells, which leads to cellular dysfunction and neuronal damage and loss. Despite this, to date, the biological process behind developing these protein inclusions must be better clarified, making the development of disease-modifying treatment impossible until this is done. Proteomics is a powerful tool to characterize the expression, structure, functions, interactions, and modifications of proteins of tissue and biological fluid, including plasma, serum, and cerebrospinal fluid. This protein-profiling characterization aims to identify disease-specific protein alteration or specific pathology-based mechanisms which may be used as markers of these conditions. Our narrative review aims to highlight the need for biomarkers and the potential use of proteomics in clinical practice for ALS-FTD spectrum disorders, considering the emerging rationale in proteomics for new drug development. Certainly, new data will emerge in the near future in this regard and support clinicians in the development of personalized medicine.

Proteomic identification of MHC class I-associated peptidome derived from non-obese diabetic mouse thymus and pancreas

The peptides repertoire presented to CD8⁺ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC I-associated peptidome (MIP), which regulates thymus development, peripheral survival and function during lifetime of CD8⁺ T cells. Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cells destruction mediated primarily by autoreactive CD8⁺ T cells. Non-obese diabetic (NOD) mouse is an important animal model of T1D. Here, we deeply analyzed the MIP derived from NOD mice thymus and pancreas, and demonstrated that the thymus MIP source proteins partially shared with the MIP source proteins derived from NOD mice pancreas and β cell line. One H-2Kd restricted peptide SLC35B1_26-34 which was shared by MIP derived from both NOD mice pancreatic tissues and islet β-cell line, but absent in MIP from NOD thymus tissues, showed ability to stimulate IFN-γ secretion and proliferation of NOD mice splenic CD8⁺ T cells. The global view of the MHC I-associated self-peptides repertoire in the thymus and pancreas of NOD mice may serve as a biological reference to identify potential autoantigens targeted by autoreactive CD8⁺ T cells in T1D. Data are available via ProteomeXchange with identifier PXD031966. SIGNIFICANCE: The peptides repertoire presented to CD8⁺ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC I-associated peptidome (MIP). The MIP presented by thymic antigen presenting cells (APCs) is crucial for shaping CD8⁺ T cell repertoire and self-tolerance, while the MIP presented by peripheral tissues and organs is not only involved in maintaining periphery CD8⁺ T cell survival and homeostasis, but also mediates immune surveillance and autoimmune responses of CD8⁺ T cells under pathological conditions. Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by the destruction of pancreatic β cells, mediated primarily by autoreactive CD8⁺ T cells. Non-obese diabetic (NOD) mouse is one of important animal models of spontaneous autoimmune diabetes that shares several key features with human T1D. The global view of the MHC I-associated self-peptides repertoire in the thymus and pancreas of NOD mice may serve as a good biological reference to identify potential autoantigens targeted by autoreactive CD8⁺ T cells in T1D. It has great significance for further clarifying the immune recognition and effect mechanism of autoreactive CD8⁺ T cells in the pathogenesis of T1D, and then developing antigen-specific immune intervention strategies.

Neutral-Coating Capillary Electrophoresis Coupled with High-Resolution Mass Spectrometry for Top-Down Identification of Hemoglobin Variants

BACKGROUND

Identification of hemoglobin (Hb) variants is of significant value in the clinical diagnosis of hemoglobinopathy. However, conventional methods for identification of Hb variants in clinical laboratories can be inadequate due to the lack of structural characterization. We describe the use of neutral-coating capillary electrophoresis coupled with high-resolution mass spectrometry (CE-HR-MS) to achieve high-performance top-down identification of Hb variants.

METHODS

An Orbitrap Q-Exactive Plus mass spectrometer was coupled with an ECE-001 capillary electrophoresis (CE) unit through an EMASS-II ion source. A PS1 neutral-coating capillary was used for CE. Samples of red blood cells were lysed in water and diluted in 10 mM ammonium formate buffer for analysis. Deconvolution of raw mass spectrometry data was carried out to merge multiple charge states and isotopic peaks of an analyte to obtain its monoisotopic mass.

RESULTS

The neutral-coating CE could baseline separate individual Hb subunits dissociated from intact Hb forms, and the HR-MS could achieve both intact-protein analysis and top-down analysis of analytes. A number of patient samples that contain Hb subunit variants were analyzed, and the variants were successfully identified using the CE-HR-MS method.

CONCLUSIONS

The CE-HR-MS method has been demonstrated as a useful tool for top-down identification of Hb variants. With the ability to characterize the primary structures of Hb subunits, the CE-HR-MS method has significant advantages to complement or partially replace the conventional methods for the identification of Hb variants.

Microfluidic nanodevices for drug sensing and screening applications

The outbreak of pandemics (e.g., severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 in 2019), influenza A viruses (H1N1 in 2009), etc.), and worldwide spike in the aging population have created unprecedented urgency for developing new drugs to improve disease treatment. As a result, extensive efforts have been made to design novel techniques for efficient drug monitoring and screening, which form the backbone of drug development. Compared to traditional techniques, microfluidics-based platforms have emerged as promising alternatives for high-throughput drug screening due to their inherent miniaturization characteristics, low sample consumption, integration, and compatibility with diverse analytical strategies. Moreover, the microfluidic-based models utilizing human cells to produce in-vitro biomimetics of the human body pave new ways to predict more accurate drug effects in humans. This review provides a comprehensive summary of different microfluidics-based drug sensing and screening strategies and briefly discusses their advantages. Most importantly, an in-depth outlook of the commonly used detection techniques integrated with microfluidic chips for highly sensitive drug screening is provided. Then, the influence of critical parameters such as sensing materials and microfluidic platform geometries on screening performance is summarized. This review also outlines the recent applications of microfluidic approaches for screening therapeutic and illicit drugs. Moreover, the current challenges and the future perspective of this research field is elaborately highlighted, which we believe will contribute immensely towards significant achievements in all aspects of drug development.

Development of a high-resolution mass-spectrometry-based method and software for human leukocyte antigen typing

Introduction

The human leukocyte antigen (HLA) system plays a critical role in the human immune system and is strongly associated with immune recognition and rejection in organ transplantation. HLA typing method has been extensively studied to increase the success rates of clinical organ transplantation. However, while polymerase chain reaction sequence-based typing (PCR-SBT) remains the gold standard, cis/trans ambiguity and nucleotide sequencing signal overlay during heterozygous typing present a problem. The high cost and low processing speed of Next Generation Sequencing (NGS) also render this approach inadequate for HLA typing.

Methods and materials

To address these limitations of the current HLA typing methods, we developed a novel typing technology based on nucleic acid mass spectrometry (MS) of HLA. Our method takes advantage of the high-resolution mass analysis function of MS and HLAMSTTs (HLA MS Typing Tags, some short fragment PCR amplification target products) with precise primer combinations.

Results

We correctly typed HLA by measuring the molecular weights of HLAMSTTs with single nucleotide polymorphisms (SNPs). In addition, we developed a supporting HLA MS typing software to design PCR primers, construct the MS database, and select the best-matching HLA typing results. With this new method, we typed 16 HLA-DQA1 samples, including 6 homozygotes and 10 heterozygotes. The MS typing results were validated by PCR-SBT.

Discussion

The MS HLA typing method is rapid, efficient, accurate, and readily applicable to typing of homozygous and heterozygous samples.

Metagenomic next-generation sequencing and proteomics analysis in pediatric viral encephalitis and meningitis

Introduction

Early and accurate identification of pathogens is essential for improved outcomes in patients with viral encephalitis (VE) and/or viral meningitis (VM).

Methods

In our research, Metagenomic next-generation sequencing (mNGS) which can identify viral pathogens unbiasedly was performed on RNA and DNA to identify potential pathogens in cerebrospinal fluid (CSF) samples from 50 pediatric patients with suspected VEs and/or VMs. Then we performed proteomics analysis on the 14 HEV-positive CSF samples and another 12 CSF samples from health controls (HCs). A supervised partial least squaresdiscriminant analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA) model was performed using proteomics data.

Results

Ten viruses in 48% patients were identified and the most common pathogen was human enterovirus (HEV) Echo18. 11 proteins overlapping between the top 20 DEPs in terms of P value and FC and the top 20 proteins in PLS-DA VIP lists were acquired.

Discussion

Our result showed mNGS has certain advantages on pathogens identification in VE and VM and our research established a foundation to identify diagnosis biomarker candidates of HEV-positive meningitis based on MS-based proteomics analysis, which could also contribute toward investigating the HEV-specific host response patterns.

Statistical and Computational Methods for Proteogenomic Data Analysis

Proteins are the functional molecules for almost all cellular and biological processes. They are also the targets of most drugs. Proteins employ complex, multilevel regulations, so their abundance levels do not well correlated with their mRNA expression levels. The structure, activity, and functional roles of proteins are affected by posttranslational modifications (PTM), which are even less correlated with mRNA expression levels than protein abundances. Comprehensive characterization of the proteomics data is critical for understanding the molecular and cellular mechanisms of biological systems and developing news therapeutics. Current large-scale proteomic profiling technologies, such as mass spectrometry, provide relative identification of peptides and proteins, with data vulnerable to outliers, batch effects, and nonrandom missingness. In order to perform high-quality proteomic data analysis, we will first introduce a data preprocessing and quality control pipeline that includes normalization, outlier detection and removal, batch effect identification and handling, and missing data imputation. Then, we will describe several statistical methods that leverage well-processed proteomic data to generate scientific discoveries, especially with an integration with genomics and transcriptomics. These methods cover topics like association analysis, network construction, clustering, and cell-type deconvolution. To demonstrate these methods, we will use the proteogenomic data from the lung squamous cell carcinoma study of the Clinical Proteomic Tumor Analysis Consortium and provide sample codes for data access and analyses.

Recent Advances in Genomics-Based Approaches for the Development of Intracellular Bacterial Pathogen Vaccines

Infectious diseases continue to be a leading cause of morbidity and mortality worldwide. The majority of infectious diseases are caused by intracellular pathogenic bacteria (IPB). Historically, conventional vaccination drives have helped control the pathogenesis of intracellular bacteria and the emergence of antimicrobial resistance, saving millions of lives. However, in light of various limitations, many diseases that involve IPB still do not have adequate vaccines. In response to increasing demand for novel vaccine development strategies, a new area of vaccine research emerged following the advent of genomics technology, which changed the paradigm of vaccine development by utilizing the complete genomic data of microorganisms against them. It became possible to identify genes related to disease virulence, genetic patterns linked to disease virulence, as well as the genetic components that supported immunity and favorable vaccine responses. Complete genomic databases, and advancements in transcriptomics, metabolomics, structural genomics, proteomics, immunomics, pan-genomics, synthetic genomics, and population biology have allowed researchers to identify potential vaccine candidates and predict their effects in patients. New vaccines have been created against diseases for which previously there were no vaccines available, and existing vaccines have been improved. This review highlights the key issues and explores the evolution of vaccines. The increasing volume of IPB genomic data, and their application in novel genome-based techniques for vaccine development, were also examined, along with their characteristics, and the opportunities and obstacles involved. Critically, the application of genomics technology has helped researchers rapidly select and evaluate candidate antigens. Novel vaccines capable of addressing the limitations associated with conventional vaccines have been developed and pressing healthcare issues are being addressed.

Multifaceted Pharmacological Potentials of Curcumin, Genistein, and Tanshinone IIA through Proteomic Approaches: An In-Depth Review

Phytochemicals possess various intriguing pharmacological properties against diverse pathological conditions. Extensive studies are on-going to understand the structural/functional properties of phytochemicals as well as the molecular mechanisms of their therapeutic function against various disease conditions. Phytochemicals such as curcumin (Cur), genistein (Gen), and tanshinone-IIA (Tan IIA) have multifaceted therapeutic potentials and various efforts are in progress to understand the molecular dynamics of their function with different tools and technologies. Cur is an active lipophilic polyphenol with pleiotropic function, and it has been shown to possess various intriguing properties including antioxidant, anti-inflammatory, anti-microbial, anticancer, and anti-genotoxic properties besides others beneficial properties. Similarly, Gen (an isoflavone) exhibits a wide range of vital functions including antioxidant, anti-inflammatory, pro-apoptotic, anti-proliferative, anti-angiogenic activities etc. In addition, Tan IIA, a lipophilic compound, possesses antioxidant, anti-angiogenic, anti-inflammatory, anticancer activities, and so on. Over the last few decades, the field of proteomics has garnered great momentum mainly attributed to the recent advancement in mass spectrometry (MS) techniques. It is envisaged that the proteomics technology has considerably contributed to the biomedical research endeavors lately. Interestingly, they have also been explored as a reliable approach to understand the molecular intricacies related to phytochemical-based therapeutic interventions. The present review provides an overview of the proteomics studies performed to unravel the underlying molecular intricacies of various phytochemicals such as Cur, Gen, and Tan IIA. This in-depth study will help the researchers in better understanding of the pharmacological potential of the phytochemicals at the proteomics level. Certainly, this review will be highly instrumental in catalyzing the translational shift from phytochemical-based biomedical research to clinical practice in the near future.

Bioinformatic Analysis of Genetic Factors from Human Blood Samples and Postmortem Brains in Parkinson's Disease

Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorders characterized by motor and nonmotor symptoms due to the selective loss of midbrain dopaminergic neurons. Pharmacological and surgical interventions have not been possible to cure PD; however, the cause of neurodegeneration remains unclear. Here, we performed and tested a multitiered bioinformatic analysis using the GEO and Proteinexchange database to investigate the gene expression involved in the pathogenesis of PD. Then we further validated individual differences in gene expression in whole blood samples that we collected in the clinic. We also made an interaction analysis and prediction for these genetic factors. There were in all 1045 genes expressing differently in PD compared with the healthy control group. Protein-protein interaction (PPI) networks showed 10 top hub genes: ACO2, MDH2, SDHA, ATP5A1, UQCRC2, PDHB, SUCLG1, NDUFS3, UQCRC1, and ATP5C1. We validated the ten hub gene expression in clinical PD patients and showed the expression of MDH2 was significantly different compared with healthy control. Besides, we also identified the expression of G6PD, GRID2, RIPK2, CUL4B, BCL6, MRPS31, GPI, and MAP 2 K1 were all significantly increased, and levels of MAPK, ELAVL1, RAB14, KLF9, ARF1, ARFGAP1, ATG7, ABCA7, SFT2D2, E2F2, MAPK7, and UHRF1 were all significantly decreased in PD. Among them, to our knowledge, we presently have the most recent and conclusive evidence that GRID2, RIPK2, CUL4B, E2F2, and ABCA7 are possible PD indicators. We confirmed several genetic factors which may be involved in the pathogenesis of PD. They could be promising markers for discriminating the PD and potential factors that may affect PD development.

Discovery and mechanism studies of a novel ATG4B inhibitor Ebselen by drug repurposing and its anti-colorectal cancer effects in mice

Cysteine protease ATG4B, a key autophagy protein, is an attractive target for colorectal cancer therapy. However, ATG4B inhibitors with higher efficiency, safety, and clear mechanism are still limited. In this study, we discovered ATG4B inhibitors based on the FDA-approved drug library through FRET-based high-throughput screening and gel-based analysis. Among the nine hits, compound Ebselen showed the most potent ATG4B inhibitory activity (IC₅₀ = 189 nM) and exhibited controllable selectivity and structural optimizable possibility against ATG4A and caspases. We then performed mass spectrometry assay and cysteine mutations to confirm that Ebselen could covalently bind to ATG4B at Cys74. Moreover, Cys292 and Cys361 instead of Cys74 are responsible for the redox-oligomerization and efficient activity inhibition of ATG4B. Ultimately through cell culture and mouse xenograft tumor models, we established the impact of Ebselen on autophagy and tumor suppression via ATG4B inhibition other than apoptosis. These results suggest that old drug Ebselen as an ATG4B inhibitor through oxidative modification may be repurposed as a promising anti-colorectal cancer drug.

Microfluidics for multiscale studies of biomolecular condensates

Membraneless organelles formed through condensation of biomolecules in living cells have become the focus of sustained efforts to elucidate their mechanisms of formation and function. These condensates perform a range of vital functions in cells and are closely connected to key processes in functional and aberrant biology. Since these systems occupy a size scale intermediate between single proteins and conventional protein complexes on the one hand, and cellular length scales on the other hand, they have proved challenging to probe using conventional approaches from either protein science or cell biology. Additionally, condensate can form, solidify and perform functions on various time-scales. From a physical point of view, biomolecular condensates are colloidal soft matter systems, and microfluidic approaches, which originated in soft condensed matter research, have successfully been used to study biomolecular condensates. This review explores how microfluidics have aided condensate research into the thermodynamics, kinetics and other properties of condensates, by offering high-throughput and novel experimental setups.

Phospho-heavy-labeled-spiketide FAIMS stepped-CV DDA (pHASED) provides real-time phosphoproteomics data to aid in cancer drug selection

Global high-throughput phosphoproteomic profiling is increasingly being applied to cancer specimens to identify the oncogenic signaling cascades responsible for promoting disease initiation and disease progression; pathways that are often invisible to genomics analysis. Hence, phosphoproteomic profiling has enormous potential to inform and improve individualized anti-cancer treatment strategies. However, to achieve the adequate phosphoproteomic depth and coverage necessary to identify the activated, and hence, targetable kinases responsible for driving oncogenic signaling pathways, affinity phosphopeptide enrichment techniques are required and often coupled with offline high-pressure liquid chromatographic (HPLC) separation prior to nanoflow liquid chromatography-tandem mass spectrometry (nLC-MS/MS). These complex and time-consuming procedures, limit the utility of phosphoproteomics for the analysis of individual cancer patient specimens in real-time, and restrict phosphoproteomics to specialized laboratories often outside of the clinical setting. To address these limitations, here we have optimized a new protocol, phospho-heavy-labeled-spiketide FAIMS Stepped-CV DDA (pHASED), that employs online phosphoproteome deconvolution using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and internal phosphopeptide standards to provide accurate label-free quantitation (LFQ) data in real-time. Compared with traditional single-shot LFQ phosphoproteomics workflows, pHASED provided increased phosphoproteomic depth and coverage (phosphopeptides = 4617 pHASED, 2789 LFQ), whilst eliminating the variability associated with offline prefractionation. pHASED was optimized using tyrosine kinase inhibitor (sorafenib) resistant isogenic FLT3-mutant acute myeloid leukemia (AML) cell line models. Bioinformatic analysis identified differential activation of the serine/threonine protein kinase ataxia-telangiectasia mutated (ATM) pathway, responsible for sensing and repairing DNA damage in sorafenib-resistant AML cell line models, thereby uncovering a potential therapeutic opportunity. Herein, we have optimized a rapid, reproducible, and flexible protocol for the characterization of complex cancer phosphoproteomes in real-time, a step towards the implementation of phosphoproteomics in the clinic to aid in the selection of anti-cancer therapies for patients.

Recent Advances in Proteomics-Based Approaches to Studying Age-Related Macular Degeneration: A Systematic Review

Age-related macular degeneration (AMD) is a common ocular disease characterized by degeneration of the central area of the retina in the elderly population. Progression and response to treatment are influenced by genetic and non-genetic factors. Proteomics is a powerful tool to study, at the molecular level, the mechanisms underlying the progression of the disease, to identify new therapeutic targets and to establish biomarkers to monitor progression and treatment effectiveness. In this work, we systematically review the use of proteomics-based approaches for the study of the molecular mechanisms underlying the development of AMD, as well as the progression of the disease and on-treatment patient monitoring. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting guidelines were followed. Proteomic approaches have identified key players in the onset of the disease, such as complement components and proteins involved in lipid metabolism and oxidative stress, but also in the progression to advanced stages, including factors related to extracellular matrix integrity and angiogenesis. Although anti-vascular endothelial growth factor (anti-VEGF)-based therapy has been crucial in the treatment of neovascular AMD, it is necessary to deepen our understanding of the underlying disease mechanisms to move forward to next-generation therapies for later-stage forms of this multifactorial disease.