Beyond mass spectrometry, the next step in proteomics

Ten "Cheat Codes" for Measuring Oxidative Stress in Humans

Formidable and often seemingly insurmountable conceptual, technical, and methodological challenges hamper the measurement of oxidative stress in humans. For instance, fraught and flawed methods, such as the thiobarbituric acid reactive substances assay kits for lipid peroxidation, rate-limit progress. To advance translational redox research, we present ten comprehensive "cheat codes" for measuring oxidative stress in humans. The cheat codes include analytical approaches to assess reactive oxygen species, antioxidants, oxidative damage, and redox regulation. They provide essential conceptual, technical, and methodological information inclusive of curated "do" and "don't" guidelines. Given the biochemical complexity of oxidative stress, we present a research question-grounded decision tree guide for selecting the most appropriate cheat code(s) to implement in a prospective human experiment. Worked examples demonstrate the benefits of the decision tree-based cheat code selection tool. The ten cheat codes define an invaluable resource for measuring oxidative stress in humans.

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

Single-Molecule Electrical Profiling of Peptides and Proteins

In recent decades, there has been a significant increase in the application of single-molecule electrical analysis platforms in studying proteins and peptides. These advanced analysis methods have the potential for deep investigation of enzymatic working mechanisms and accurate monitoring of dynamic changes in protein configurations, which are often challenging to achieve in ensemble measurements. In this work, the prominent research progress in peptide and protein-related studies are surveyed using electronic devices with single-molecule/single-event sensitivity, including single-molecule junctions, single-molecule field-effect transistors, and nanopores. In particular, the successful commercial application of nanopores in DNA sequencing has made it one of the most promising techniques in protein sequencing at the single-molecule level. From single peptides to protein complexes, the correlation between their electrical characteristics, structures, and biological functions is gradually being established. This enables to distinguish different molecular configurations of these biomacromolecules through real-time electrical monitoring of their life activities, significantly improving the understanding of the mechanisms underlying various life processes.

Amplifiable protein identification via residue-resolved barcoding and composition code counting

Ultrasensitive protein identification is of paramount importance in basic research and clinical diagnostics but remains extremely challenging. A key bottleneck in preventing single-molecule protein sequencing is that, unlike the revolutionary nucleic acid sequencing methods that rely on the polymerase chain reaction (PCR) to amplify DNA and RNA molecules, protein molecules cannot be directly amplified. Decoding the proteins via amplification of certain fingerprints rather than the intact protein sequence thus represents an appealing alternative choice to address this formidable challenge. Herein, we report a proof-of-concept method that relies on residue-resolved DNA barcoding and composition code counting for amplifiable protein fingerprinting (AmproCode). In AmproCode, selective types of residues on peptides or proteins are chemically labeled with a DNA barcode, which can be amplified and quantified via quantitative PCR. The operation generates a relative ratio as the residue-resolved 'composition code' for each target protein that can be utilized as the fingerprint to determine its identity from the proteome database. We developed a database searching algorithm and applied it to assess the coverage of the whole proteome and secretome via computational simulations, proving the theoretical feasibility of AmproCode. We then designed the residue-specific DNA barcoding and amplification workflow, and identified different synthetic model peptides found in the secretome at as low as the fmol/L level for demonstration. These results build the foundation for an unprecedented amplifiable protein fingerprinting method. We believe that, in the future, AmproCode could ultimately realize single-molecule amplifiable identification of trace complex samples without further purification, and it may open a new avenue in the development of next-generation protein sequencing techniques.

Investigating Antiprotozoal Chemotherapies with Novel Proteomic Tools-Chances and Limitations: A Critical Review

Identification of drug targets and biochemical investigations on mechanisms of action are major issues in modern drug development. The present article is a critical review of the classical "one drug"-"one target" paradigm. In fact, novel methods for target deconvolution and for investigation of resistant strains based on protein mass spectrometry have shown that multiple gene products and adaptation mechanisms are involved in the responses of pathogens to xenobiotics rather than one single gene or gene product. Resistance to drugs may be linked to differential expression of other proteins than those interacting with the drug in protein binding studies and result in complex cell physiological adaptation. Consequently, the unraveling of mechanisms of action needs approaches beyond proteomics. This review is focused on protozoan pathogens. The conclusions can, however, be extended to chemotherapies against other pathogens or cancer.

Unraveling NEK4 as a Potential Drug Target in Schizophrenia and Bipolar I Disorder: A Proteomic and Genomic Approach

BACKGROUND AND HYPOTHESIS

Investigating the shared brain protein and genetic components of schizophrenia (SCZ) and bipolar I disorder (BD-I) presents a unique opportunity to understand the underlying pathophysiological processes and pinpoint potential drug targets.

STUDY DESIGN

To identify overlapping susceptibility brain proteins in SCZ and BD-I, we carried out proteome-wide association studies (PWAS) and Mendelian Randomization (MR) by integrating human brain protein quantitative trait loci with large-scale genome-wide association studies for both disorders. We utilized transcriptome-wide association studies (TWAS) to determine the consistency of mRNA-protein dysregulation in both disorders. We applied pleiotropy-informed conditional false discovery rate (pleioFDR) analysis to identify common risk genetic loci for SCZ and BD-I. Additionally, we performed a cell-type-specific analysis in the human brain to detect risk genes notably enriched in distinct brain cell types. The impact of risk gene overexpression on dendritic arborization and axon length in neurons was also examined.

STUDY RESULTS

Our PWAS identified 42 proteins associated with SCZ and 14 with BD-I, among which NEK4, HARS2, SUGP1, and DUS2 were common to both conditions. TWAS and MR analysis verified the significant risk gene NEK4 for both SCZ and BD-I. PleioFDR analysis further supported genetic risk loci associated with NEK4 for both conditions. The cell-type specificity analysis revealed that NEK4 is expressed on the surface of glutamatergic neurons, and its overexpression enhances dendritic arborization and axon length in cultured primary neurons.

CONCLUSIONS

These findings underscore a shared genetic origin for SCZ and BD-I, offering novel insights for potential therapeutic target identification.

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Trypsin Encapsulation in the Zeolitic Imidazolate Framework for Low-Molecular Weight Protein Analysis with High Selectivity and Efficiency

Low-molecular weight proteins (LWPs) are important sources of biological information in biomarkers, signaling molecules, and pathology. However, the separation and analysis of LWPs in complex biological samples are challenging, mainly due to their low abundance and the complex sample pretreatment procedure. Herein, trypsin modified by poly(acrylic acid) (PAA) was encapsulated by a zeolitic imidazolate framework (ZIF-L). Mesopores were formed on the ZIF-L with the introduction of PAA. An alternative strategy for separation and pretreatment of LWPs was developed based on the prepared ZIF-L-encapsulated trypsin with adjustable pore size. The mesoporous structure of the prepared materials selectively excluded high-molecular weight proteins from the reaction system, allowing LWPs to enter the pores and react with the internal trypsin, resulting in an improved separation efficiency. The hydrophobicity of the ZIF-L simplified the digestion process by inducing significant structural changes in substrate proteins. In addition, the enzymatic activity was significantly enhanced by the developed encapsulation method that maintained the enzyme conformation, allowed low mass transfer resistance, and possessed a high enzyme-to-substrate ratio. As a result, the ZIF-L-encapsulated trypsin can achieve highly selective separation, valid denaturation, and efficient digestion of LWPs in a short time by simply mixing with substrate proteins, greatly simplifying the separation and pretreatment process of the traditional hydrolysis method. The prepared materials and the developed strategy demonstrated an excellent size-selective assay performance in model protein mixtures, showing great potential in the application of proteomics analysis.

Use of Transcriptional Signatures to Differentiate Pathogen-Specific and Treatment-Specific Host Responses in Patients With Bacterial Bloodstream Infections

BACKGROUND

Clinical outcomes in bacterial bloodstream infections (BSIs) are influenced by bacterial species, host immunity, and antibiotic therapy. The mechanisms by which such factors influence outcomes are poorly understood. We aimed to identify bacterial- and antibiotic-specific host transcriptional signatures in patients with bacterial BSI.

METHODS

RNA sequencing was performed on blood samples from patients with BSI due to gram-negative (GN) versus gram-positive (GP) pathogens: Escherichia coli (n = 30) or Klebsiella pneumoniae (n = 28) versus methicillin-susceptible Staphylococcus aureus (MSSA) (n = 24) or methicillin-resistant S. aureus (MRSA) (n = 58). Patients were matched by age, sex, and race.

RESULTS

No significant host transcriptome differences were detected in patients with E. coli versus K. pneumoniae BSI, so these were considered together as GN BSI. Relative to S. aureus BSI, patients with GN BSI had increased activation of the classic complement system. However, the most significant signal was a reduction in host transcriptional signatures involving mitochondrial energy transduction and oxidative burst in MRSA versus MSSA. This attenuated host transcriptional signature remained after controlling for antibiotic therapy.

CONCLUSIONS

Given the importance of immune cellular energetics and reactive oxygen species in eliminating hematogenous or intracellular MRSA, these findings may offer insights into its persistence relative to other bacterial BSIs.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Full-length single-molecule protein fingerprinting

Proteins are the primary functional actors of the cell. While proteoform diversity is known to be highly biologically relevant, current protein analysis methods are of limited use for distinguishing proteoforms. Mass spectrometric methods, in particular, often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate fluorescence resonance energy transfer (FRET)-based single-molecule protein fingerprinting to map the location of individual amino acids and post-translational modifications within single full-length protein molecules. Our data show that both intrinsically disordered proteins and folded globular proteins can be fingerprinted with a subnanometer resolution, achieved by probing the amino acids one by one using single-molecule FRET via DNA exchange. This capability was demonstrated through the analysis of alpha-synuclein, an intrinsically disordered protein, by accurately quantifying isoforms in mixtures using a machine learning classifier, and by determining the locations of two O-GlcNAc moieties. Furthermore, we demonstrate fingerprinting of the globular proteins Bcl-2-like protein 1, procalcitonin and S100A9. We anticipate that our ability to perform proteoform identification with the ultimate sensitivity may unlock exciting new venues in proteomics research and biomarker-based diagnosis.

Decoding plant specialized metabolism: new mechanistic insights

Secondary metabolite (SM) production provides biotic and abiotic stress resistance and enables plants to adapt to the environment. Biosynthesis of these metabolites involves a complex interplay between transcription factors (TFs) and regulatory elements, with emerging evidence suggesting an integral role for chromatin dynamics. Here we review key TFs and epigenetic regulators that govern SM biosynthesis in different contexts. We summarize relevant emerging technologies and results from the model species arabidopsis (Arabidopsis thaliana) and outline aspects of regulation that may also function in food, feed, fiber, oil, or industrial crop plants. Finally, we highlight how effective translation of fundamental knowledge from model to non-model species can benefit understanding of SM production in a variety of ecological, agricultural, and pharmaceutical contexts.

Orientational Pathways during Protein Translocation through Polymer-Modified Nanopores

Protein translocation through nanopores holds significant promise for applications in biotechnology, biomolecular analysis, and medicine. However, the interpretation of signals generated by the translocation of the protein remains challenging. In this way, it is crucial to gain a comprehensive understanding on how macromolecules translocate through a nanopore and to identify what are the critical parameters that govern the process. In this study, we investigate the interplay between protein charge regulation, orientation, and nanopore surface modifications using a theoretical framework that allows us to explicitly take into account the acid-base reactions of the titrable amino acids in the proteins and in the polyelectrolytes grafted to the nanopore surface. Our goal is to thoroughly characterize the translocation process of different proteins (GFP, β-lactoglobulin, lysozyme, and RNase) through nanopores modified with weak polyacids. Our calculations show that the charge regulation mechanism exerts a profound effect on the translocation process. The pH-dependent interactions between proteins and charged polymers within the nanopore lead to diverse free energy landscapes with barriers, wells, and flat regions dictating translocation efficiency. Comparison of different proteins allows us to identify the significance of protein isoelectric point, size, and morphology in the translocation behavior. Taking advantage of these insights, we propose pH-responsive nanopores that can load proteins at one pH and release them at another, offering opportunities for controlled protein delivery, separation, and sensing applications.

Protein Deceleration and Sequencing Using Si3N4-CNT Hybrid Nanopores

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions and is of utmost importance in molecular diagnostics and medication development. Nanopores have become an effective tool for single molecule sensing, however, the weak charge and non-uniform charge distribution of protein make capturing and sensing very challenging, which poses a significant obstacle to the development of nanopore-based protein sequencing. In this study, to facilitate capturing of the unfolded protein, highly charged peptide was employed in our simulations, we found that the velocity of unfolded peptide translocating through a hybrid nanopore composed of silicon nitride membrane and carbon nanotube is much slower compared to bare silicon nitride nanopore, it is due to the significant interaction between amino acids and the surface of carbon nanotube. Moreover, by introducing variations in the charge states at the boundaries of carbon nanotube nanopores, the competition and combination of the electrophoretic and electroosmotic flows through the nanopores could be controlled, we then successfully regulated the translocation velocity of unfolded proteins through the hybrid nanopores. The proposed hybrid nanopore effectively retards the translocation velocity of protein through it, facilitates the acquisition of ample information for accurate amino acid identification.

Cyanobacterial Proteomics: Diversity and Dynamics

Cyanobacteria (oxygenic photoautrophs) comprise a diverse group holding significance both environmentally and for biotechnological applications. The utilization of proteomic techniques has significantly influenced investigations concerning cyanobacteria. Application of proteomics allows for large-scale analysis of protein expression and function within cyanobacterial systems. The cyanobacterial proteome exhibits tremendous functional, spatial, and temporal diversity regulated by multiple factors that continuously modify protein abundance, post-translational modifications, interactions, localization, and activity to meet the dynamic needs of these tiny blue greens. Modern mass spectrometry-based proteomics techniques enable system-wide examination of proteome complexity through global identification and high-throughput quantification of proteins. These powerful approaches have revolutionized our understanding of proteome dynamics and promise to provide novel insights into integrated cellular behavior at an unprecedented scale. In this Review, we present modern methods and cutting-edge technologies employed for unraveling the spatiotemporal diversity and dynamics of cyanobacterial proteomics with a specific focus on the methods used to analyze post-translational modifications (PTMs) and examples of dynamic changes in the cyanobacterial proteome investigated by proteomic approaches.

Sequentially-Activated Antibodies Based on Programmable DNA Tags for Rapid Multiplexed Protein Imaging

The achievement of rapid multiplexed protein imaging is limited by the use of stimulating reagents, extensive incubating and washing steps, and the low fluorescence intensity of targets. In this study, sequentially-activated DNA tags are developed and combined them with primary antibodies using signal enhancement strategies to create sequentially-activated antibodies (SAAs). These SAAs enable rapid, wash-free sequential imaging of different protein targets. The samples are pre-processed to label all targets of interest with SAAs simultaneously, and the signal is turned ON for only one target in each stage. The sequential imaging of multiple targets is achieved through wash-free strand displacement reactions that exhibit rapid kinetics with t1/2  < 10 s in a cellular context. Remarkably, this method successfully demonstrates sequential imaging of nine different protein targets within just a few minutes. This all-in-one platform for multiplexed protein imaging holds great promise for diverse applications in immunofluorescence imaging.

Starch treatment improves the salivary proteome for subject identification purposes

Identification of subjects, including perpetrators, is one of the most crucial goals of forensic science. Saliva is among the most common biological fluids found at crime scenes, containing identifiable components. DNA has been the most prominent identifier to date, but its analysis can be complex due to low DNA yields and issues preserving its integrity at the crime scene. Proteins are emerging as viable candidates for subject identification. Previous work has shown that the salivary proteome of the least-abundant proteins may be helpful for subject identification, but more optimized techniques are needed. Among them is removing the most abundant proteins, such as salivary α-amylase. Starch treatment of saliva samples elicited the removal of this enzyme and that of glycosylated, low-molecular-weight proteins, proteases, and immunoglobulins, resulting in a saliva proteome profile enriched with a subset of proteins, allowing a more reliable and nuanced subject identification.

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

Narrowing Signal Distribution by Adamantane Derivatization for Amino Acid Identification Using an α-Hemolysin Nanopore

The rapid progress in nanopore sensing has sparked interest in protein sequencing. Despite recent notable advancements in amino acid recognition using nanopores, chemical modifications usually employed in this process still need further refinements. One of the challenges is to enhance the chemical specificity to avoid downstream misidentification of amino acids. By employing adamantane to label proteinogenic amino acids, we developed an approach to fingerprint individual amino acids using the wild-type α-hemolysin nanopore. The unique structure of adamantane-labeled amino acids (ALAAs) improved the spatial resolution, resulting in distinctive current signals. Various nanopore parameters were explored using a machine-learning algorithm and achieved a validation accuracy of 81.3% for distinguishing nine selected amino acids. Our results not only advance the effort in single-molecule protein characterization using nanopores but also offer a potential platform for studying intrinsic and variant structures of individual molecules.

Shotgun Characterization of the Circulating IgM Antigenome of an Infectious Pathogen by Immunocapture-LC-MS/MS from Dried Serum Spots

One of the main challenges in compiling the complete collection of protein antigens from pathogens for the selection of vaccine candidates or intervention targets is to acquire a broad enough representation of them to be recognized by the highly diversified immunoglobulin repertoire in human populations. Dried serum spot sampling (DSS) retains a large repertoire of circulating immunoglobulins from each individual that can be representative of a population, according to the sample size. In this work, shotgun proteomics of an infectious pathogen based on DSS sampling coupled with IgM immunoprecipitation, liquid chromatography-mass spectrometry (LC-MS/MS), and bioinformatic analyses was combined to characterize the circulating IgM antigenome. Serum samples from a malaria endemic region at different clinical statuses were studied to optimize IgM binding efficiency and antibody leaching by varying serum/immunomagnetic bead ratios and elution conditions. The method was validated using Plasmodium falciparum extracts identifying 110 of its IgM-reactive antigens while minimizing the presence of human proteins and antibodies. Furthermore, the IgM antigen recognition profile differentiated between malaria-infected and noninfected individuals at the time of sampling. We conclude that a shotgun proteomics approach offers advantages in providing a high-throughput, reliable, and clean way to identify IgM-recognized antigens from trace amounts of serum. The mass spectrometry raw data and metadata have been deposited with ProteomeXchange via MassIVE with the PXD identifier PXD043800.

Glucocorticoid and Adrenergic Receptor Distribution Across Human Organs and Tissues: A Map for Stress Transduction

OBJECTIVE

Psychosocial stress is transduced into disease risk through energy-dependent release of hormones from the hypothalamic-pituitary-adrenal and sympathetic-adrenal-medullary axes. The levels of glucocorticoid and adrenergic hormones, together with the sensitivity of tissues to their signaling, define stress responses. To understand existing pathways responsible for the psychobiological transduction of stressful experiences, we provide a quantitative whole-body map of glucocorticoid and adrenergic receptor (AR) expression.

METHODS

We systematically examined gene expression levels for the glucocorticoid receptor (GR), α- and β-ARs (AR-α1B, AR-α2B AR-β2, and AR-β3), across 55 different organs using the Human Protein Atlas and Human Proteome Map datasets. Given that mitochondria produce the energy required to respond to stress, we leveraged the Human Protein Atlas and MitoCarta3.0 data to examine the link between stress hormone receptor density and mitochondrial gene expression. Finally, we tested the functional interplay between GR activation and AR expression in human fibroblast cells.

RESULTS

The GR was expressed ubiquitously across all investigated organ systems, whereas AR subtypes showed lower and more localized expression patterns. Receptor co-regulation, meaning the correlated gene expression of multiple stress hormone receptors, was found between GR and AR-α1B, as well as between AR-α1B and AR-α2B. In cultured human fibroblasts, activating the GR selectively increased AR-β2 and AR-α1B expression. Consistent with the known energetic cost of stress responses, GR and AR expressions were positively associated with the expression of specific mitochondrial pathways.

CONCLUSIONS

Our results provide a cartography of GR and AR expression across the human body. Because stress-induced GR and AR signaling triggers energetically expensive cellular pathways involving energy-transforming mitochondria, the tissue-specific expression and co-expression patterns of hormone receptor subtypes may in part determine the resilience or vulnerability of different organ systems.

iProPhos: A Web-Based Interactive Platform for Integrated Proteome and Phosphoproteome Analysis

Large-scale omics studies have generated a wealth of mass spectrometry-based proteomics data, which provide additional insights into disease biology spanning genomic boundaries. However, there is a notable lack of web-based analysis and visualization tools that facilitate the reutilization of these data. Given this challenge, we present iProPhos, a user-friendly web server to deliver interactive and customizable functionalities. iProPhos incorporates a large number of samples, including 1444 tumor samples and 746 normal samples across 12 cancer types, sourced from the Clinical Proteomic Tumor Analysis Consortium. Additionally, users can also upload their own proteomics/phosphoproteomics data for analysis and visualization. In iProPhos, users can perform profiling plotting and differential expression, patient survival, clinical feature-related, and correlation analyses, including protein-protein, mRNA-protein, and kinase-substrate correlations. Furthermore, functional enrichment, protein-protein interaction network, and kinase-substrate enrichment analyses are accessible. iProPhos displays the analytical results in interactive figures and tables with various selectable parameters. It is freely accessible at http://longlab-zju.cn/iProPhos without login requirement. We present two case studies to demonstrate that iProPhos can identify potential drug targets and upstream kinases contributing to site-specific phosphorylation. Ultimately, iProPhos allows end-users to leverage the value of big data in cancer proteomics more effectively and accelerates the discovery of novel therapeutic targets.

Molecular sensitised probe for amino acid recognition within peptide sequences

The combination of low-temperature scanning tunnelling microscopy with a mass-selective electro-spray ion-beam deposition established the investigation of large biomolecules at nanometer and sub-nanometer scale. Due to complex architecture and conformational freedom, however, the chemical identification of building blocks of these biopolymers often relies on the presence of markers, extensive simulations, or is not possible at all. Here, we present a molecular probe-sensitisation approach addressing the identification of a specific amino acid within different peptides. A selective intermolecular interaction between the sensitiser attached at the tip-apex and the target amino acid on the surface induces an enhanced tunnelling conductance of one specific spectral feature, which can be mapped in spectroscopic imaging. Density functional theory calculations suggest a mechanism that relies on conformational changes of the sensitiser that are accompanied by local charge redistributions in the tunnelling junction, which, in turn, lower the tunnelling barrier at that specific part of the peptide.

Universal method for the isolation of microvessels from frozen brain tissue: A proof-of-concept multiomic investigation of the neurovasculature

The neurovascular unit, comprised of vascular cell types that collectively regulate cerebral blood flow to meet the needs of coupled neurons, is paramount for the proper function of the central nervous system. The neurovascular unit gatekeeps blood-brain barrier properties, which experiences impairment in several central nervous system diseases associated with neuroinflammation and contributes to pathogenesis. To better understand function and dysfunction at the neurovascular unit and how it may confer inflammatory processes within the brain, isolation and characterization of the neurovascular unit is needed. Here, we describe a singular, standardized protocol to enrich and isolate microvessels from archived snap-frozen human and frozen mouse cerebral cortex using mechanical homogenization and centrifugation-separation that preserves the structural integrity and multicellular composition of microvessel fragments. For the first time, microvessels are isolated from postmortem ventromedial prefrontal cortex tissue and are comprehensively investigated as a structural unit using both RNA sequencing and Liquid Chromatography with tandem mass spectrometry (LC-MS/MS). Both the transcriptome and proteome are obtained and compared, demonstrating that the isolated brain microvessel is a robust model for the NVU and can be used to generate highly informative datasets in both physiological and disease contexts.

The function of alternative splicing in the proteome: rewiring protein interactomes to put old functions into new contexts

Alternative splicing affects more than 95% of multi-exon genes in the human genome. These changes affect the proteome in a myriad of ways. Here, we review our understanding of the breadth of these changes from their effect on protein structure to their influence on interactions. These changes encompass effects on nucleic acid binding in the nucleus to protein-carbohydrate interactions in the extracellular milieu, altering interactions involving all major classes of biological molecules. Protein isoforms have profound influences on cellular and tissue physiology, for example, by shaping neuronal connections, enhancing insulin secretion by pancreatic beta cells and allowing for alternative viral defense strategies in stem cells. More broadly, alternative splicing enables repurposing proteins from one context to another and thereby contributes to both the evolution of new traits as well as the creation of disease-specific interactomes that drive pathological phenotypes. In this Review, we highlight this universal character of alternative splicing as a central regulator of protein function with implications for almost every biological process.

Photothermal Microscopy and Spectroscopy with Nanomechanical Resonators

In nanomechanical photothermal absorption spectroscopy and microscopy, the measured substance becomes a part of the detection system itself, inducing a nanomechanical resonance frequency shift upon thermal relaxation. Suspended, nanometer-thin ceramic or 2D material resonators are innately highly sensitive thermal detectors of localized heat exchanges from substances on their surface or integrated into the resonator itself. Consequently, the combined nanoresonator-analyte system is a self-measuring spectrometer and microscope responding to a substance's transfer of heat over the entire spectrum for which it absorbs, according to the intensity it experiences. Limited by their own thermostatistical fluctuation phenomena, nanoresonators have demonstrated sufficient sensitivity for measuring trace analyte as well as single particles and molecules with incoherent light or focused and wide-field coherent light. They are versatile in their design, support various sampling methods-potentially including hydrated sample encapsulation-and hyphenation with other spectroscopic methods, and are capable in a wide range of applications including fingerprinting, separation science, and surface sciences.

Inclusion of Porous Graphitic Carbon Chromatography Yields Greater Protein Identification and Compartment and Process Coverage and Enables More Reflective Protein-Level Label-Free Quantitation

The ubiquity of mass spectrometry-based bottom-up proteomic analyses as a component of biological investigation mandates the validation of methodologies that increase acquisition efficiency, improve sample coverage, and enhance profiling depth. Chromatographic separation is often ignored as an area of potential improvement, with most analyses relying on traditional reversed-phase liquid chromatography (RPLC); this consistent reliance on a single chromatographic paradigm fundamentally limits our view of the observable proteome. Herein, we build upon early reports and validate porous graphitic carbon chromatography (PGC) as a facile means to substantially enhance proteomic coverage without changes to sample preparation, instrument configuration, or acquisition methods. Analysis of offline fractionated cell line digests using both separations revealed an increase in peptide and protein identifications by 43% and 24%, respectively. Increased identifications provided more comprehensive coverage of cellular components and biological processes independent of protein abundance, highlighting the substantial quantity of proteomic information that may go undetected in standard analyses. We further utilize these data to reveal that label-free quantitative analyses using RPLC separations alone may not be reflective of actual protein constituency. Together, these data highlight the value and comprehension offered through PGC-MS proteomic analyses. RAW proteomic data have been uploaded to the MassIVE repository with the primary accession code MSV000091495.

50 shades of oxidative stress: A state-specific cysteine redox pattern hypothesis

Oxidative stress is biochemically complex. Like primary colours, specific reactive oxygen species (ROS) and antioxidant inputs can be mixed to create unique "shades" of oxidative stress. Even a minimal redox module comprised of just 12 (ROS & antioxidant) inputs and 3 outputs (oxidative damage, cysteine-dependent redox-regulation, or both) yields over half a million "shades" of oxidative stress. The present paper proposes the novel hypothesis that: state-specific shades of oxidative stress, such as a discrete disease, are associated with distinct tell-tale cysteine oxidation patterns. The patterns are encoded by many parameters, from the identity of the oxidised proteins, the cysteine oxidation type, and magnitude. The hypothesis is conceptually grounded in distinct ROS and antioxidant inputs coalescing to produce unique cysteine oxidation outputs. And considers the potential biological significance of the holistic cysteine oxidation outputs. The literature supports the existence of state-specific cysteine oxidation patterns. Measuring and manipulating these patterns offer promising avenues for advancing oxidative stress research. The pattern inspired hypothesis provides a framework for understanding the complex biochemical nature of state-specific oxidative stress.

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.

High-performance peptide and disulfide mapping by direct injection of intact proteins using on-line coupled UV-liquid chromatography microdroplet mass spectrometry (UVLC-MMS)

Microdroplet mass spectrometry (MMS), achieving ultra-fast enzyme digestion in the ionization source, holds great promises for innovating protein analysis. Here, in-depth protein characterization is demonstrated by direct injection of intact protein mixtures via on-line coupling MMS with capillary C4 liquid chromatography (LC) containing UV windows (UVLC-MMS) through an enzyme introduction tee. We showed complete sets of peptides of individual proteins (hemoglobin, bovine serum albumin, and ribonuclease A) in a mixture could be obtained in one injection. Such full (100%) sequence coverage, however, could not be achieved by conventional nanoLC-MS method using bottom-up approach with single enzyme. Moreover, direct injection of a chaperone α-crystalline (α-Cry) complex yielded identification of post-translational modifications including novel sites and semi-quantitative characterization including 3:1 stoichiometry ratio of αA- and αB-Cry sub-units and ∼1.4 phosphorylation/subunit on S45 (novel site) and S122 (main site) of αA-Cry, ∼0.7 phosphorylation/subunit on S19 (main site) and S45 of αB-Cry, as well as 100% acetylation on both N-termini of each subunits by matching the mass and retention time of the intact and its digested peptides. Furthermore, trifluoroacetic acid was able to be used in the mobile phase with UVLC-MMS to improve the separation of differentially reduced intact species and detectability of the droplet-digested products. This allowed us to completely map four disulfide linkages of ribonuclease A based on collision-induced dissociation of disulfide clusters, some of which would otherwise not be detected, preventing scrambling or shuffling errors arising from lengthy bulk solution digestion by the bottom-up approach. Integration of UVLC and MMS greatly improves droplet digestion efficiency and MS detection, enabling highly efficient workflow for in-depth and accurate protein characterization.

Multi-pass, single-molecule nanopore reading of long protein strands with single-amino acid sensitivity

The ability to sequence single protein molecules in their native, full-length form would enable a more comprehensive understanding of proteomic diversity. Current technologies, however, are limited in achieving this goal. Here, we establish a method for long-range, single-molecule reading of intact protein strands on a commercial nanopore sensor array. By using the ClpX unfoldase to ratchet proteins through a CsgG nanopore, we achieve single-amino acid level sensitivity, enabling sequencing of combinations of amino acid substitutions across long protein strands. For greater sequencing accuracy, we demonstrate the ability to reread individual protein molecules, spanning hundreds of amino acids in length, multiple times, and explore the potential for high accuracy protein barcode sequencing. Further, we develop a biophysical model that can simulate raw nanopore signals a priori, based on amino acid volume and charge, enhancing the interpretation of raw signal data. Finally, we apply these methods to examine intact, folded protein domains for complete end-to-end analysis. These results provide proof-of-concept for a platform that has the potential to identify and characterize full-length proteoforms at single-molecule resolution.

Common Post-translational Modifications (PTMs) of Proteins: Analysis by Up-to-Date Analytical Techniques with an Emphasis on Barley

Post-translational modifications (PTMs) of biomacromolecules can be useful for understanding the processes by which a relatively small number of individual genes in a particular genome can generate enormous biological complexity in different organisms. The proteomes of barley and the brewing process were investigated by different techniques. However, their diverse and complex PTMs remain understudied. As standard analytical approaches have limitations, innovative analytical approaches need to be developed and applied in PTM studies. To make further progress in this field, it is necessary to specify the sites of modification, as well as to characterize individual isoforms with increased selectivity and sensitivity. This review summarizes advances in the PTM analysis of barley proteins, particularly those involving mass spectrometric detection. Our focus is on monitoring phosphorylation, glycation, and glycosylation, which critically influence functional behavior in metabolism and regulation in organisms.

E. coli outer membrane protein T (OmpT) nanopore for peptide sensing

Peptide detection methods with facility and high sensitivity are essential for diagnosing disease associated with peptide biomarkers. Nanopore sensing technology had emerged as a low cost, high-throughput, and scalable tool for peptide detection. The omptins family proteins which can form β-barrel pores have great potentials to be developed as nanopore biosensor. However, there are no study about the channel properties of E. coli OmpT and the development of OmpT as a nanopore biosensor. In this study, the OmpT biological nanopore channel was constructed with a conductance of 1.49 nS in 500 mM NaCl buffer and a three-step gating phenomenon under negative voltage higher than 100 mV and then was developed as a peptide biosensor which can detect peptide without the interfere of ssDNA and dNTPs. The OmpT constructed in this study has potential application in peptide detection, and also provides a new idea for the detection of peptides using the specific binding ability of protease.

Considerable slowdown of short DNA fragment translocation across a protein nanopore using pH-induced generation of enthalpic traps inside the permeation pathway

A pressing challenge in the realm of nanopore-based sensing technologies for nucleic acid characterization has been the cheap and efficient control of analyte translocation. To address this, a plethora of methods were tested, including mutagenesis, molecular motors, enzymes, or the optimization of experimental conditions. Herein, we present a paradigm exploiting the manipulation of electrostatic interactions between 22-mer single-stranded DNAs (22_ssDNA) and low pH-induced charges in the alpha-hemolysin (α-HL) nanopore, to efficiently control the passage of captured molecules. We discovered that in electrolytes buffered at pH = 5 and pH = 4.5 where the nanopore's vestibule and lumen become oppositely charged as compared to that at neutral pH, the electrostatic anchoring at these regions of a 22_ssDNA fragment leads to a dramatic increase of the translocation time, orders of magnitude larger compared to that at neutral pH. This pH-dependent tethering effect is reversible, side invariant, and sensitive to the ionic strength and ssDNA contour length. In the long run, our discovery has the potential to provide a simple read-out of the sequence of bases pertaining to short nucleotide sequences, thus extending the efficacy of current nanopore-based sequencers.

Robust and scalable single-molecule protein sequencing with fluorosequencing

The need to accurately survey proteins and their modifications with ever higher sensitivities, particularly in clinical settings with limited samples, is spurring development of new single molecule proteomics technologies. Fluorosequencing is one such highly parallelized single molecule peptide sequencing platform, based on determining the sequence positions of select amino acid types within peptides to enable their identification and quantification from a reference database. Here, we describe substantial improvements to fluorosequencing, including identifying fluorophores compatible with the sequencing chemistry, mitigating dye-dye interactions through the use of extended polyproline linkers, and developing an end-to-end workflow for sample preparation and sequencing. We demonstrate by fluorosequencing peptides in mixtures and identifying a target neoantigen from a database of decoy MHC peptides, highlighting the potential of the technology for high sensitivity clinical applications.

Engineering Biological Nanopore Approaches toward Protein Sequencing

Biotechnological innovations have vastly improved the capacity to perform large-scale protein studies, while the methods we have for identifying and quantifying individual proteins are still inadequate to perform protein sequencing at the single-molecule level. Nanopore-inspired systems devoted to understanding how single molecules behave have been extensively developed for applications in genome sequencing. These nanopore systems are emerging as prominent tools for protein identification, detection, and analysis, suggesting realistic prospects for novel protein sequencing. This review summarizes recent advances in biological nanopore sensors toward protein sequencing, from the identification of individual amino acids to the controlled translocation of peptides and proteins, with attention focused on device and algorithm development and the delineation of molecular mechanisms with the aid of simulations. Specifically, the review aims to offer recommendations for the advancement of nanopore-based protein sequencing from an engineering perspective, highlighting the need for collaborative efforts across multiple disciplines. These efforts should include chemical conjugation, protein engineering, molecular simulation, machine-learning-assisted identification, and electronic device fabrication to enable practical implementation in real-world scenarios.

Are We Ready to Reclassify Crohn's Disease Using Molecular Classification?

Crohn's disease (CD) is a type of inflammatory bowel disease. The number of IBD cases worldwide was estimated to be 4.9 million in 2019. CD exhibits heterogeneity in clinical presentation, anatomical involvement, disease behaviour, clinical course and response to treatment. The classical description of CD involves transmural inflammation with skip lesions anywhere along the entire gastrointestinal tract. The complexity and heterogeneity of Crohn's disease is not currently reflected in the conventional classification system. Though the knowledge of Crohn's pathophysiology remains far from understood, the established complex interplay of the omics-genomics, transcriptomics, proteomics, epigenomics, metagenomics, metabolomics, lipidomics and immunophenomics-provides numerous targets for potential molecular markers of disease. Advancing technology has enabled identification of small molecules within these omics, which can be extrapolated to differentiate types of Crohn's disease. The multi-omic future of Crohn's disease is promising, with potential for advancements in understanding of its pathogenesis and implementation of personalised medicine.

Laser capture microdissection for biomedical research: towards high-throughput, multi-omics, and single-cell resolution

Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context, significantly enhancing our understanding of the intricate and multifaceted biological system. With an increasing focus on spatial heterogeneity, there is a growing need for unbiased, spatially resolved omics technologies. Laser capture microdissection (LCM) is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest (ROIs) from heterogeneous tissues, with resolutions ranging from single cells to cell populations. Thus, LCM has been widely used for studying the cellular and molecular mechanisms of diseases. This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research. Key attributes of application cases are also highlighted, such as throughput and spatial resolution. In addition, we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research, disease diagnosis, and targeted therapy from the perspective of high-throughput, multi-omics, and single-cell resolution.

Proteomics and disease network associations evaluation of environmentally relevant Bisphenol A concentrations in a human 3D neural stem cell model

Bisphenol A (BPA) exposure is associated with a plethora of neurodevelopmental abnormalities and brain disorders. Previous studies have demonstrated BPA-induced perturbations to critical neural stem cell (NSC) characteristics, such as proliferation and differentiation, although the underlying molecular mechanisms remain under debate. The present study evaluated the effects of a repeated-dose exposure of environmentally relevant BPA concentrations during the in vitro 3D neural induction of human induced pluripotent stem cells (hiPSCs), emulating a chronic exposure scenario. Firstly, we demonstrated that our model is suitable for NSC differentiation during the early stages of embryonic brain development. Our morphological image analysis showed that BPA exposure at 0.01, 0.1 and 1 µM decreased the average spheroid size by day 21 (D21) of the neural induction, while no effect on cell viability was detected. No alteration to the rate of the neural induction was observed based on the expression of key neural lineage and neuroectodermal transcripts. Quantitative proteomics at D21 revealed several differentially abundant proteins across all BPA-treated groups with important functions in NSC proliferation and maintenance (e.g., FABP7, GPC4, GAP43, Wnt-8B, TPPP3). Additionally, a network analysis demonstrated alterations to the glycolytic pathway, potentially implicating BPA-induced changes to glycolytic signalling in NSC proliferation impairments, as well as the pathophysiology of brain disorders including intellectual disability, autism spectrum disorders, and amyotrophic lateral sclerosis (ALS). This study enhances the current understanding of BPA-related NSC aberrations based mostly on acute, often high dose exposures of rodent in vivo and in vitro models and human GWAS data in a novel human 3D cell-based model with real-life scenario relevant prolonged and low-level exposures, offering further mechanistic insights into the ramifications of BPA exposure on the developing human brain and consequently, later life neurological disorders.

Spatial tissue proteomics reveals distinct landscapes of heterogeneity in cutaneous papillomavirus-induced keratinocyte carcinomas

Infection with certain cutaneous human papillomaviruses (HPV), in conjunction with chronic ultraviolet (UV) exposure, are the major cofactors of non-melanoma skin cancer (NMSC), the most frequent cancer type worldwide. Cutaneous squamous cell carcinomas (SCCs) as well as tumors in general represent three-dimensional entities determined by both temporal and spatial constraints. Whole tissue proteomics is a straightforward approach to understand tumorigenesis in better detail, but studies focusing on different progression states toward a dedifferentiated SCC phenotype on a spatial level are rare. Here, we applied an innovative proteomic workflow on formalin-fixed, paraffin-embedded (FFPE) epithelial tumors derived from the preclinical animal model Mastomys coucha. This rodent is naturally infected with its genuine cutaneous papillomavirus and closely mimics skin carcinogenesis in the context of cutaneous HPV infections in humans. We deciphered cellular networks by comparing diverse epithelial tissues with respect to their differentiation level and infection status. Our study reveals novel regulatory proteins and pathways associated with virus-induced tumor initiation and progression of SCCs. This approach provides the basis to better comprehend the multistep process of skin carcinogenesis.

Performance benchmarking microplate-immunoassays for quantifying target-specific cysteine oxidation reveals their potential for understanding redox-regulation and oxidative stress

The antibody-linked oxi-state assay (ALISA) for quantifying target-specific cysteine oxidation can benefit specialist and non-specialist users. Specialists can benefit from time-efficient analysis and high-throughput target and/or sample n-plex capacities. The simple and accessible "off-the-shelf" nature of ALISA brings the benefits of oxidative damage assays to non-specialists studying redox-regulation. Until performance benchmarking establishes confidence in the "unseen" microplate results, ALISA is unlikely to be widely adopted. Here, we implemented pre-set pass/fail criteria to benchmark ALISA by evaluating immunoassay performance in diverse contexts. ELISA-mode ALISA assays were accurate, reliable, and sensitive. For example, the average inter-assay CV for detecting 20%- and 40%-oxidised PRDX2 or GAPDH standards was 4.6% (range: 3.6-7.4%). ALISA displayed target-specificity. Immunodepleting the target decreased the signal by ∼75%. Single-antibody formatted ALISA failed to quantify the matrix-facing alpha subunit of the mitochondrial ATP synthase. However, RedoxiFluor quantified the alpha subunit displaying exceptional performance in the single-antibody format. ALISA discovered that (1) monocyte-to-macrophage differentiation amplified PRDX2-oxidation in THP-1 cells and (2) exercise increased GAPDH-specific oxidation in human erythrocytes. The "unseen" microplate data were "seen-to-be-believed" via orthogonal visually displayed immunoassays like the dimer method. Finally, we established target (n = 3) and sample (n = 100) n-plex capacities in ∼4 h with 50-70 min hands-on time. Our work showcases the potential of ALISA to advance our understanding of redox-regulation and oxidative stress.

The role of clinical glyco(proteo)mics in precision medicine

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.

Advances in single-molecule junctions as tools for chemical and biochemical analysis

The development of miniaturized electronics has led to the design and construction of powerful experimental platforms capable of measuring electronic properties to the level of single molecules, along with new theoretical concepts to aid in the interpretation of the data. A new area of activity is now emerging concerned with repurposing the tools of molecular electronics for applications in chemical and biological analysis. Single-molecule junction techniques, such as the scanning tunnelling microscope break junction and related single-molecule circuit approaches have a remarkable capacity to transduce chemical information from individual molecules, sampled in real time, to electrical signals. In this Review, we discuss single-molecule junction approaches as emerging analytical tools for the chemical and biological sciences. We demonstrate how these analytical techniques are being extended to systems capable of probing chemical reaction mechanisms. We also examine how molecular junctions enable the detection of RNA, DNA, and traces of proteins in solution with limits of detection at the zeptomole level.

Exploring structural features and potential lipid interactions of Pseudomonas aeruginosa type three secretion effector PemB by spectroscopic and calorimetric experiments

Type Three Secretion System (T3SS) is a sophisticated nano-scale weapon utilized by several gram negative bacteria under stringent spatio-temporal regulation to manipulate and evade host immune systems in order to cause infection. To the best of our knowledge, this present study is the first report where we embark upon characterizing inherent features of native type three secretion effector protein PemB through biophysical techniques. Herein, first, we demonstrate binding affinity of PemB for phosphoinositides through isothermal calorimetric titrations. Second, we shed light on its strong homo-oligomerization propensity in aqueous solution through multiple biophysical methods. Third, we also employ several spectroscopic techniques to delineate its disordered and helical conformation. Lastly, we perform a phylogenetic analysis of this new effector to elucidate evolutionary relationship with other organisms. Taken together, our results shall surely contribute to our existing knowledge of Pseudomonas aeruginosa secretome.

Nanopore Detection Using Supercharged Polypeptide Molecular Carriers

The analysis at the single-molecule level of proteins and their interactions can provide critical information for understanding biological processes and diseases, particularly for proteins present in biological samples with low copy numbers. Nanopore sensing is an analytical technique that allows label-free detection of single proteins in solution and is ideally suited to applications, such as studying protein-protein interactions, biomarker screening, drug discovery, and even protein sequencing. However, given the current spatiotemporal limitations in protein nanopore sensing, challenges remain in controlling protein translocation through a nanopore and relating protein structures and functions with nanopore readouts. Here, we demonstrate that supercharged unstructured polypeptides (SUPs) can be genetically fused with proteins of interest and used as molecular carriers to facilitate nanopore detection of proteins. We show that cationic SUPs can substantially slow down the translocation of target proteins due to their electrostatic interactions with the nanopore surface. This approach enables the differentiation of individual proteins with different sizes and shapes via characteristic subpeaks in the nanopore current, thus facilitating a viable route to use polypeptide molecular carriers to control molecular transport and as a potential system to study protein-protein interactions at the single-molecule level.

Bringing synapses into focus: Recent advances in synaptic imaging and mass-spectrometry for studying synaptopathy

Synapses are integral for healthy brain function and are becoming increasingly recognized as key structures in the early stages of brain disease. Understanding the pathological processes driving synaptic dysfunction will unlock new therapeutic opportunities for some of the most devastating diseases of our time. To achieve this we need a solid repertoire of imaging and molecular tools to interrogate synaptic biology at greater resolution. Synapses have historically been examined in small numbers, using highly technical imaging modalities, or in bulk, using crude molecular approaches. However, recent advances in imaging techniques are allowing us to analyze large numbers of synapses, at single-synapse resolution. Furthermore, multiplexing is now achievable with some of these approaches, meaning we can examine multiple proteins at individual synapses in intact tissue. New molecular techniques now allow accurate quantification of proteins from isolated synapses. The development of increasingly sensitive mass-spectrometry equipment means we can now scan the synaptic molecular landscape almost in totality and see how this changes in disease. As we embrace these new technical developments, synapses will be viewed with clearer focus, and the field of synaptopathy will become richer with insightful and high-quality data. Here, we will discuss some of the ways in which synaptic interrogation is being facilitated by methodological advances, focusing on imaging, and mass spectrometry.

Using Artificial Intelligence to Better Predict and Develop Biomarkers

Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, transcripts, proteins, and metabolites. Furthermore, improvements in artificial intelligence (AI) have made the interpretation of large omics data sets easier and improved analysis. Use of omics and AI in biomarker discovery can aid clinicians by identifying markers of risk for developing HF, monitoring care, determining prognosis, and developing druggable targets. Combined, AI has the power to improve HF patient care.