Theoretical Assessment of Indistinguishable Peptides in Mass Spectrometry-Based Proteomics

Mass-spectrometry-based proteomics has advanced with the integration of experimental and predicted spectral libraries, which have significantly improved peptide identification in complex search spaces. However, challenges persist in distinguishing some peptides with close retention times and nearly identical fragmentation patterns. In this study, we conducted a theoretical assessment to quantify the prevalence of indistinguishable peptides within the human canonical proteome and immunopeptidome using state-of-the-art retention time and spectrum prediction models. By quantifying the proportion of peptides posing challenges to unequivocal identification, we set the theoretical nonaccessible portion within a given proteome, and underscore the effectiveness of contemporary analytical methodologies in resolving the complexity of the human proteome and immunopeptidome via mass spectrometry.

Achieving Electron Capture Dissociation in the Radio Frequency Linear Ion Trap without the Assistance of a Magnetic Field─A Simulation Study

It is extremely difficult to inject a low-energy electron beam into a conventional radiofrequency (RF) linear ion trap for electron capture dissociation (ECD) without using a magnetic field to focus the electrons. In this study, the dynamic process of electrons in an RF field during their injection and transmission through a linear ion trap was simulated to determine the range of the RF phase where the electrons can be decelerated to meet the energy requirement for ECD. The ECD time window was expanded by applying a time-dependent compensation voltage to the cathode. The relationship between the cathode voltage and the phase of the RF voltage was determined. The ECD time window was increased to 49.4% of the total RF cycle after applying a compensation voltage. Between the phases of RF voltage of 0 and 0.975 π, at least 98.7% of electrons can be injected into the ECD reaction zone, and 94% of them had an energy less than 3 eV. The range of electron energy can also easily be shifted upward to enable hot electron capture dissociation.

Navigating the Proteomic Landscape of Menopause: A Review

Background and Objectives: Proteomics encompasses the exploration of protein composition, regulation, function, and pathways. Its influence spans diverse clinical fields and holds promise in addressing various women's health conditions, including cancers, osteoporosis, and cardiovascular disorders. However, no comprehensive summary of proteomics and menopausal health exists. Our objective was to summarize proteomic profiles associated with diseases and disorders in peri- and postmenopausal women. Materials and Methods: We conducted a comprehensive search of databases including PubMed, Google Scholar, the Cochrane database, Elsevier, and ScienceDirect until 2022. A total of 253 studies were identified, and 41 studies met the inclusion criteria to identify data of interest. These included the study design, disease, and proteomics/proteins of significance, as described by the authors. Results: The 41 studies covered diverse areas, including bone disorders (10 studies), cardiovascular diseases (5 studies), oncological malignancies (10 studies), and various conditions, such as obesity, nonalcoholic liver disease, the effects of hormone replacement therapy, and neurological diseases (16 studies). The results of our study indicate that proteomic profiles correlate with heart disease in peri- and postmenopausal women, with distinct sex differences. Furthermore, proteomic profiles significantly differ between women with and without osteoporosis. Additionally, patients with breast, ovarian, and endometrial cancer exhibit notable variations in proteomic profiles compared to those without these conditions. Conclusions: Proteomics has the potential to enhance risk assessment and disease monitoring in peri- and postmenopausal women. By analyzing unique protein profiles, clinicians can identify individuals with heightened susceptibility to specific diseases or those already affected by established conditions. This review suggests that there is sufficient preliminary data related to proteomics in peri- and postmenopausal women for early identification of cardiovascular disease, osteoporosis, and cancers, disease monitoring, and tailoring individualized therapies. Rigorous validation studies involving large populations are essential before drawing definitive conclusions regarding the clinical applicability of proteomic findings.

The Carrier Proteome Should Be Reassessed for Each Mass Analyzer Architecture

A clever utilization of classic proteomics reagents now allows the effective amplification of the peptide sequencing potential in shotgun proteomics. The application of this method has helped usher in the exciting new field of single cell proteomics. While it was easy to first think that this approach was finally the answer for the polymerase chain reaction in protein chemistry, limitations were carefully described by the authors and others. A study by Cheung et al. systematically identified the consequences of higher concentration carrier proteomes and defined the "carrier proteome limit" [Cheung et al. Nat. Methods 2021, 18, 76]. While this work has been replicated by others, every analysis published to date has used a variation of the same mass analyzer. When the same analysis is performed on alternative instruments, these limits appear to be very different and can be attributed to defined characteristics of each mass analyzer. Specifically, in mass analyzers with a higher relative intrascan linear dynamic range, increased carrier channels appear less detrimental to quantitative accuracy. As such, we may be limiting the power of isobaric peptide signal "amplification" by restricting ourselves to traditional mass analyzer options for shotgun proteomics.

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.

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Mass Spectrometry of Collagen-Containing Allogeneic Human Bone Tissue Material

The current paper highlights the active development of tissue engineering in the field of the biofabrication of living tissue analogues through 3D-bioprinting technology. The implementation of the latter is impossible without important products such as bioinks and their basic components, namely, hydrogels. In this regard, tissue engineers are searching for biomaterials to produce hydrogels with specified properties both in terms of their physical, mechanical and chemical properties and in terms of local biological effects following implantation into an organism. One of such effects is the provision of the optimal conditions for physiological reparative regeneration by the structural components that form the basis of the biomaterial. Therefore, qualitative assessment of the composition of the protein component of a biomaterial is a significant task in tissue engineering and bioprinting. It is important for predicting the behaviour of printed constructs in terms of their gradual resorption followed by tissue regeneration due to the formation of a new extracellular matrix. One of the most promising natural biomaterials with significant potential in the production of hydrogels and the bioinks based on them is the polymer collagen of allogeneic origin, which plays an important role in maintaining the structural and biological integrity of the extracellular matrix, as well as in the morphogenesis and cellular metabolism of tissues, giving them the required mechanical and biochemical properties. In tissue engineering, collagen is widely used as a basic biomaterial because of its availability, biocompatibility and facile combination with other materials. This manuscript presents the main results of a mass spectrometry analysis (proteomic assay) of the lyophilized hydrogel produced from the registered Lyoplast® bioimplant (allogeneic human bone tissue), which is promising in the field of biotechnology. Proteomic assays of the investigated lyophilized hydrogel sample showed the presence of structural proteins (six major collagen fibers of types I, II, IV, IX, XXVII, XXVIII were identified), extracellular matrix proteins, and mRNA-stabilizing proteins, which participate in the regulation of transcription, as well as inducer proteins that mediate the activation of regeneration, including the level of circadian rhythm. The research results offer a new perspective and indicate the significant potential of the lyophilized hydrogels as an effective alternative to synthetic and xenogeneic materials in regenerative medicine, particularly in the field of biotechnology, acting as a matrix and cell-containing component of bioinks for 3D bioprinting.

Single cell proteomics by mass spectrometry reveals deep epigenetic insight into the actions of an orphan histone deacetylase inhibitor

Epigenetic programming has been shown to play a role in nearly every human system and disease where anyone has thought to look. However, the levels of heterogeneity at which epigenetic or epiproteomic modifications occur at single cell resolution across a population remains elusive. While recent advances in sequencing technology have allowed between 1 and 3 histone post-translational modifications to be analyzed in each single cell, over twenty separate chemical PTMs are known to exist, allowing thousands of possible combinations. Single cell proteomics by mass spectrometry (SCP) is an emerging technology in which hundreds or thousands of proteins can be directly quantified in typical human cells. As the proteins detected and quantified by SCP are heavily biased toward proteins of highest abundance, chromatin proteins are an attractive target for analysis. To this end, I applied SCP to the analysis of cancer cells treated with mocetinostat, a class specific histone deacetylase inhibitor. I find that 16 PTMs can be confidently identified and localized with high site specificity in single cells. In addition, the high abundance of histone proteins allows higher throughput methods to be utilized for SCP than previously described. While quantitative accuracy suffers when analyzing more than 700 cells per day, 9 histone proteins can be measured in single cells analyzed at even 3,500 cells per day, a throughput 10-fold greater than any previous report. In addition, the unbiased global approach utilized herein identifies a previously uncharacterized response to this drug through the S100-A8/S100-A9 protein complex partners. This response is observed in nearly every cell of the over 1,000 analyzed in this study, regardless of the relative throughput of the method utilized. While limitations exist in the methods described herein, current technologies can easily improve upon the results presented here to allow comprehensive analysis of histone PTMs to be performed in any mass spectrometry lab. All raw and processed data described in this study has been made publicly available through the ProteomeXchange/MASSIVE repository system as MSV000093434.

What proteomics has taught us about honey bee (Apis mellifera) health and disease

The Western honey bee, Apis mellifera, is currently navigating a gauntlet of environmental pressures, including the persistent threat of parasites, pathogens, and climate change - all of which compromise the vitality of honey bee colonies. The repercussions of their declining health extend beyond the immediate concerns of apiarists, potentially imposing economic burdens on society through diminished agricultural productivity. Hence, there is an imperative to devise innovative monitoring techniques for assessing the health of honey bee populations. Proteomics, recognized for its proficiency in biomarker identification and protein-protein interactions, is poised to play a pivotal role in this regard. It offers a promising avenue for monitoring and enhancing the resilience of honey bee colonies, thereby contributing to the stability of global food supplies. This review delves into the recent proteomic studies of A. mellifera, highlighting specific proteins of interest and envisioning the potential of proteomics to improve sustainable beekeeping practices amidst the challenges of a changing planet.

Paradigm Shift: Major Role of Ion-Pairing-Dependent Size Exclusion Effects in Bottom-Up Proteomics Reversed-Phase Peptide Separations

Can reversed-phase peptide retention be the same for C8 and C18 columns? or increase for otherwise identical columns with a smaller surface area? Can replacing trifluoroacetic acid (TFA) with formic acid (FA) improve the peak shape? According to our common understanding of peptide chromatography, absolutely not. Surprisingly, a thorough comparison of the peptide separation selectivity of 100 and 120 Å fully porous C18 sorbents to maximize the performance of our in-house proteomics LC-MS/MS setup revealed an unexpectedly higher peptide retentivity for a wider pore packing material, despite it having a smaller surface area. Concurrently, the observed increase in peptide retention─which drives variation in separation selectivity between 100 and 120 Å pore size materials─was more pronounced for smaller peptides. These findings contradict the central dogmas that underlie the development of all peptide RP-HPLC applications: (i) a larger surface area leads to higher retention and (ii) increasing the pore size should benefit the retention of larger analytes. Based on our intriguing findings, we compared reversed-phase high-performance liquid chromatography peptide retention for a total of 20 columns with pore sizes between 60 and 300 Å using FA- and TFA-based eluents. Our results unequivocally attest that the larger size of ion pairs in FA- vs TFA-based eluents leads to the observed impact on selectivity and peptide retention. For FA, peptide retention peaks at 200 Å pore size, compared to between 120 and 200 Å for TFA. However, the decrease in retention for narrow-pore particles is more profound in FA. Our findings suggest that common assumptions about analyte size and accessible surface area should be revisited for ion-pair RP separation of small peptides, typical for proteomic applications that are predominantly applying FA eluents. Hybrid silica-based materials with pore sizes of 130-200 Å should be specifically targeted for bottom-up proteomic applications to obtain both superior peak shape and peptide retentivity. This challenging task of attaining the best RPLC column for proteomics calls for closer collaboration between LC column manufacturers and proteomic LC specialists.

Investigation of Structure-Stabilizing Elements in Proteins by Ion Mobility Mass Spectrometry and Collision-Induced Unfolding

A recently developed proteolytic reactor, designed for protein structural investigation, was coupled to ion mobility mass spectrometry to monitor collisional cross section (CCS) evolution of model proteins undergoing trypsin-mediated mono enzymatic digestion. As peptides are released during digestion, the CCS of the remaining protein structure may deviate from the classical 2/3 power of the CCS-mass relationship for spherical structures. The classical relationship between CCS and mass (CCS = A × M2/3) for spherical structures, assuming a globular shape in the gas phase, may deviate as stabilizing elements are lost during digestion. In addition, collision-induced unfolding (CIU) experiments on partially digested proteins provided insights into the CCS resilience in the gas phase to ion activation, potentially due to the presence of stabilizing elements. The study initially investigated a model peptide ModBea (3 kDa), assessing the impact of disulfide bridges on CCS resilience in both reduced and oxidized forms. Subsequently, β-lactoglobulin (2 disulfide bridges), calmodulin (Ca2+ coordination cation), and cytochrome c (heme) were selected to investigate the influence of common structuring elements on CCS resilience. CIU experiments probed the unfolding process, evaluating the effect of losing specific peptides on the energy landscapes of partially digested proteins. Comparisons of the TWCCSN2→He to trend curves describing the CCS/mass relationship revealed that proteins with structure-stabilizing elements consistently exhibit TWCCSN2→He and greater resilience toward CIU compared to proteins lacking these elements. The integration of online digestion, ion mobility, and CIU provides a valuable tool for identifying structuring elements in biopolymers in the gas phase.

The One Hour Human Proteome

We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS1 scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.

Multiple ion isolation and accumulation events for selective chemical noise reduction and dynamic range enhancement in MALDI imaging mass spectrometry

Abundant chemical noise in MALDI imaging mass spectrometry experiments can impede the detection of less abundant compounds of interest. This chemical noise commonly originates from the MALDI matrix as well as other endogenous compounds present in high concentrations and/or with high ionization efficiencies. MALDI imaging mass spectrometry of biological tissues measures numerous biomolecular compounds that exist in a wide range of concentrations in vivo. When ion trapping instruments are used, highly abundant ions can dominate the charge capacity and lead to space charge effects that hinder the dynamic range and detection of lowly abundant compounds of interest. Gas-phase fractionation has been previously utilized in mass spectrometry to isolate and enrich target analytes. Herein, we have characterized the use of multiple continuous accumulations of selected ions (Multi CASI) to reduce the abundance of chemical noise and diminish the effects of space charge in MALDI imaging mass spectrometry experiments. Multi CASI utilizes the mass-resolving capability of a quadrupole mass filter to perform multiple sequential ion isolation events prior to a single mass analysis of the combined ion population. Multi CASI was used to improve metabolite and lipid detection in the MALDI imaging mass spectrometry analysis of rat brain tissue.

The omics era: a nexus of untapped potential for Mendelian chromatinopathies

The OMICs cascade describes the hierarchical flow of information through biological systems. The epigenome sits at the apex of the cascade, thereby regulating the RNA and protein expression of the human genome and governs cellular identity and function. Genes that regulate the epigenome, termed epigenes, orchestrate complex biological signaling programs that drive human development. The broad expression patterns of epigenes during human development mean that pathogenic germline mutations in epigenes can lead to clinically significant multi-system malformations, developmental delay, intellectual disabilities, and stem cell dysfunction. In this review, we refer to germline developmental disorders caused by epigene mutation as "chromatinopathies". We curated the largest number of human chromatinopathies to date and our expanded approach more than doubled the number of established chromatinopathies to 179 disorders caused by 148 epigenes. Our study revealed that 20.6% (148/720) of epigenes cause at least one chromatinopathy. In this review, we highlight key examples in which OMICs approaches have been applied to chromatinopathy patient biospecimens to identify underlying disease pathogenesis. The rapidly evolving OMICs technologies that couple molecular biology with high-throughput sequencing or proteomics allow us to dissect out the causal mechanisms driving temporal-, cellular-, and tissue-specific expression. Using the full repertoire of data generated by the OMICs cascade to study chromatinopathies will provide invaluable insight into the developmental impact of these epigenes and point toward future precision targets for these rare disorders.

Native mass spectrometry analysis of conjugated HSA and BSA complexes with various flavonoids

Mass spectrometry was used to study the binding interaction between serum albumin proteins (BSA and HSA) and flavone dyes, which is known to induce large fluorescence signals for protein detection. By electrospray ionization mass spectrometry (ESI-MS), multiple charged species/states could be produced in ammonium acetate buffer, while preserving the native structures of the proteins. Subsequent introduction of a flavone dye into the buffered solution resulted in an immediate interaction, forming the respective protein-dye conjugates associated by non-covalent interactions. Formation of protein-dye conjugates induced a notable response in the ESI-MS spectra, including changes in both the charge states and molecular mass of the protein species. The resulting data pointed out that the protein-flavone dye maintained a 1 : 1 ratio in the conjugate, although multiple binding sites for drug molecules are present in albumin proteins.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Protein biomarkers for root length and root dry mass on chromosomes 4A and 7A in wheat

Improving the wheat (Triticum aestivum L.) root system is important for enhancing grain yield and climate resilience. Total root length (RL) and root dry mass (RM) significantly contribute to water and nutrient acquisition directly impacting grain yield and stress tolerance. This study used label-free quantitative proteomics to identify proteins associated with RL and RM in wheat near-isogenic lines (NILs). NIL pair 6 had 113 and NIL pair 9 had 30 differentially abundant proteins (DAPs). Three of identified DAPs located within the targeted genomic regions (GRs) of NIL pairs 6 (qDT.4A.1) and 9 (QHtscc.ksu-7A), showed consistent gene expressions at the protein and mRNA transcription (qRT-PCR) levels for asparagine synthetase (TraesCS4A02G109900), signal recognition particle 19 kDa protein (TraesCS7A02G333600) and 3,4-dihydroxy-2-butanone 4-phosphate synthase (TraesCS7A02G415600). This study discovered, for the first time, the involvement of these proteins as candidate biomarkers for increased RL and RM in wheat. However, further functional validation is required to ascertain their practical applicability in wheat root breeding. SIGNIFICANCE OF THE STUDY: Climate change has impacted global demand for wheat (Triticum aestivum L.). Root traits such as total root length (RL) and root dry mass (RM) are crucial for water and nutrient uptake and tolerance to abiotic stresses such as drought, salinity, and nutrient imbalance in wheat. Improving RL and RM could significantly enhance wheat grain yield and climate resilience. However, breeding for these traits has been limited by lack of appropriate root phenotyping methods, advanced genotypes, and the complex nature of the wheat genome. In this study, we used a semi-hydroponic root phenotyping system to collect accurate root data, near-isogenic lines (NILs; isolines with similar genetic backgrounds but contrasting target genomic regions (GRs)) and label-free quantitative proteomics to explore the molecular mechanisms underlying high RL and RM in wheat. We identified differentially abundant proteins (DAPs) and their molecular pathways in NIL pairs 6 (GR: qDT.4A.1) and 9 (GR: QHtscc.ksu-7A), providing a foundation for further molecular investigations. Furthermore, we identified three DAPs within the target GRs of the NIL pairs with differential expression at the transcript level, as confirmed by qRT-PCR analysis which could serve as candidate protein biomarkers for RL and RM improvement.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

Microfluidics enabled multi-omics triple-shot mass spectrometry for cell-based therapies

In recent years, cell-based therapies have transformed medical treatment. These therapies present a multitude of challenges associated with identifying the mechanism of action, developing accurate safety and potency assays, and achieving low-cost product manufacturing at scale. The complexity of the problem can be attributed to the intricate composition of the therapeutic products: living cells with complex biochemical compositions. Identifying and measuring critical quality attributes (CQAs) that impact therapy success is crucial for both the therapy development and its manufacturing. Unfortunately, current analytical methods and tools for identifying and measuring CQAs are limited in both scope and speed. This Perspective explores the potential for microfluidic-enabled mass spectrometry (MS) systems to comprehensively characterize CQAs for cell-based therapies, focusing on secretome, intracellular metabolome, and surfaceome biomarkers. Powerful microfluidic sampling and processing platforms have been recently presented for the secretome and intracellular metabolome, which could be implemented with MS for fast, locally sampled screening of the cell culture. However, surfaceome analysis remains limited by the lack of rapid isolation and enrichment methods. Developing innovative microfluidic approaches for surface marker analysis and integrating them with secretome and metabolome measurements using a common analytical platform hold the promise of enhancing our understanding of CQAs across all "omes," potentially revolutionizing cell-based therapy development and manufacturing for improved efficacy and patient accessibility.

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics

Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, personalized medicine, systems biology and biomedical applications. By combining MS with different proteomics approaches such as immunopurification MS, immunopeptidomics, and total protein proteomics, researchers can gain insights into protein-protein interactions, immune responses, cellular processes, and disease mechanisms. The application of MS-based proteomics in these areas continues to advance our understanding of protein function, cellular signaling, and complex biological systems. Data analysis for mass spectrometry is a critical process that includes identifying and quantifying proteins and peptides and exploring biological functions for these proteins in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analysis. ProtPipe provides downstream analysis including identifying differential abundance proteins and peptides, pathway enrichment analysis, protein-protein interaction analysis, and MHC1-peptide binding affinity. ProtPipe generates annotated tables and diagnostic visualizations from statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. ProtPipe is well-documented open-source software and is available at https://github.com/NIH-CARD/ProtPipe , accompanied by a web interface.

The Potential of Meta-Proteomics and Artificial Intelligence to Establish the Next Generation of Probiotics for Personalized Healthcare

The symbiosis of probiotic bacteria with humans has rendered various health benefits while providing nutrition and a suitable environment for their survival. However, the probiotics must survive unfavorable gut conditions to exert beneficial effects. The intrinsic resistance of probiotics to survive harsh conditions results from a myriad of proteins. Interaction of microbial proteins with the host is indispensable for modulating the gut microbiome, such as interaction with cell receptors and protective action against pathogens. The complex interplay of proteins should be unraveled by utilizing metaproteomic strategies. The contribution of probiotics to health is now widely accepted. However, due to the inconsistency of generalized probiotics, contemporary research toward precision probiotics has gained momentum for customized treatment. This review explores the application of metaproteomics and AI/ML algorithms in resolving multiomics data analysis and in silico prediction of microbial features for screening specific beneficial probiotic organisms. Implementing these integrative strategies could augment the potential of precision probiotics for personalized healthcare.

Proteomic analyses of venom from a Spider Hawk, Pepsis decorata

Background

The composition of the venom from solitary wasps is poorly known, although these animals are considered sources of bioactive substances. Until the present moment, there is only one proteomic characterization of the venom of wasps of the family Pompilidae and this is the first proteomic characterization for the genus Pepsis.

Methods

To elucidate the components of Pepsis decorata venom, the present work sought to identify proteins using four different experimental conditions, namely: (A) crude venom; (B) reduced and alkylated venom; (C) trypsin-digested reduced and alkylated venom, and; (D) chymotrypsin-digested reduced and alkylated venom. Furthermore, three different mass spectrometers were used (Ion Trap-Time of Flight, Quadrupole-Time of Flight, and Linear Triple Quadruple).

Results

Proteomics analysis revealed the existence of different enzymes related to the insect's physiology in the venom composition. Besides toxins, angiotensin-converting enzyme (ACE), hyaluronidase, and Kunitz-type inhibitors were also identified.

Conclusion

The data showed that the venom of Pepsis decorata is mostly composed of proteins involved in the metabolism of arthropods, as occurs in parasitic wasps, although some classical toxins were recorded, and among them, for the first time, ACE was found in the venom of solitary wasps. This integrative approach expanded the range of compounds identified in protein analyses, proving to be efficient in the proteomic characterization of little-known species. It is our understanding that the current work will provide a solid base for future studies dealing with other Hymenoptera venoms.

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.

Advances in mass spectrometry-based multi-scale metabolomic methodologies and their applications in biological and clinical investigations

Metabolomics is a nascent field of inquiry that emerged in the late 20th century. It encompasses the comprehensive profiling of metabolites across a spectrum of organisms, ranging from bacteria and cells to tissues. The rapid evolution of analytical methods and data analysis has greatly accelerated progress in this dynamic discipline over recent decades. Sophisticated techniques such as liquid chromatograph mass spectrometry (MS), gas chromatograph MS, capillary electrophoresis MS, and nuclear magnetic resonance serve as the cornerstone of metabolomic analysis. Building upon these methods, a plethora of modifications and combinations have emerged to propel the advancement of metabolomics. Despite this progress, scrutinizing metabolism at the single-cell or single-organelle level remains an arduous task over the decades. Some of the most thrilling advancements, such as single-cell and single-organelle metabolic profiling techniques, offer profound insights into the intricate mechanisms within cells and organelles. This allows for a comprehensive study of metabolic heterogeneity and its pivotal role in multiple biological processes. The progress made in MS imaging has enabled high-resolution in situ metabolic profiling of tissue sections and even individual cells. Spatial reconstruction techniques enable the direct representation of metabolic distribution and alteration in three-dimensional space. The application of novel metabolomic techniques has led to significant breakthroughs in biological and clinical studies, including the discovery of novel metabolic pathways, determination of cell fate in differentiation, anti-aging intervention through modulating metabolism, metabolomics-based clinicopathologic analysis, and surgical decision-making based on on-site intraoperative metabolic analysis. This review presents a comprehensive overview of both conventional and innovative metabolomic techniques, highlighting their applications in groundbreaking biological and clinical studies.

Affinity Purification and Molecular Characterization of Angiotensin-Converting Enzyme (ACE)-Inhibitory Peptides from Takifugu flavidus

An affinity chromatography filler of CNBr-activated Sepharose 4B-immobilized ACE was used to purify ACE-inhibitory peptides from Takifugu flavidus protein hydrolysate (<1 kDa). Twenty-four peptides with an average local confidence score (ALC) ≥ 80% from bounded components (eluted by 1 M NaCl) were identified by LC-MS/MS. Among them, a novel peptide, TLRFALHGME, with ACE-inhibitory activity (IC50 = 93.5 µmol·L-1) was selected. Molecular docking revealed that TLRFALHGME may interact with the active site of ACE through H-bond, hydrophobic, and electrostatic interactions. The total binding energy (ΔGbinding) of TLRFALHGME was estimated to be -82.7382 kJ·mol-1 by MD simulations, indicating the favorable binding of peptides with ACE. Furthermore, the binding affinity of TLRFALHGME to ACE was determined by surface plasmon resonance (SPR) with a Kd of 80.9 µmol, indicating that there was a direct molecular interaction between them. TLRFALHGME has great potential for the treatment of hypertension.

Smart sampling as the "Spot-on" Method for LC-MS protein analysis from dried blood spots

This perspective explores the feasibility of smart sampling with dried blood spots for the determination of proteins and peptides from human biomatrices using liquid chromatography coupled to mass spectrometry for clinical purposes. The focus is on innovative approaches to transform filter paper from a mere sample carrier to an active element in sample preparation, with the aim of reducing the need for extensive and intensive sample preparation in the conventional sense. Specifically, we discuss the use of modified cellulose to integrate sample preparation at an early stage of sample handling. The use of paper immobilized with either trypsin or monoclonal antibodies for protein digestion and affinity clean-up is discussed as a potential benefit of starting sample preparation instantly at the moment of sampling to optimize time efficiency and enable faster analysis, diagnosis, and follow-up of patients.

Exploiting ion-mobility mass spectrometry for unraveling proteome complexity

Ion mobility spectrometry-mass spectrometry (IMS-MS) is experiencing rapid growth in proteomic studies, driven by its enhancements in dynamic range and throughput, increasing the quantitation precision, and the depth of proteome coverage. The core principle of ion mobility spectrometry is to separate ions in an inert gas under the influence of an electric field based on differences in drift time. This minireview provides an introduction to IMS operation modes and a description of advantages and limitations is presented. Moreover, the principles of trapped IMS-MS (TIMS-MS), including parallel accumulation-serial fragmentation are discussed. Finally, emerging applications linked to TIMS focusing on sample throughput (in clinical proteomics) and sensitivity (single-cell proteomics) are reviewed, and the possibilities of intact protein analysis are discussed.

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.

Global quantification of newly synthesized proteins reveals cell type- and inhibitor-specific effects on protein synthesis inhibition

Manipulation of protein synthesis is commonly applied to uncover protein functions and cellular activities. Multiple inhibitors with distinct mechanisms have been widely investigated and employed in bio-related research, but it is extraordinarily challenging to measure and evaluate the synthesis inhibition efficiencies of individual proteins by different inhibitors at the proteome level. Newly synthesized proteins are the immediate and direct products of protein synthesis, and thus their comprehensive quantification provides a unique opportunity to study protein inhibition. Here, we systematically investigate protein inhibition and evaluate different popular inhibitors, i.e. cycloheximide, puromycin, and anisomycin, through global quantification of newly synthesized proteins in several types of human cells (A549, MCF-7, Jurkat, and THP-1 cells). The inhibition efficiencies of protein synthesis are comprehensively measured by integrating azidohomoalanine-based protein labeling, selective enrichment, a boosting approach, and multiplexed proteomics. The same inhibitor results in dramatic variation of the synthesis inhibition efficiencies for different proteins in the same cells, and each inhibitor exhibits unique preferences. Besides cell type- and inhibitor-specific effects, some universal rules are unraveled. For instance, nucleolar and ribosomal proteins have relatively higher inhibition efficiencies in every type of cells treated with each inhibitor. Moreover, proteins intrinsically resistant or sensitive to the inhibition are identified and found to have distinct functions. Systematic investigation of protein synthesis inhibition in several types of human cells by different inhibitors provides valuable information about the inhibition of protein synthesis, advancing our understanding of inhibiting protein synthesis.

Next-Generation Sequencing for Venomics: Application of Multi-Enzymatic Limited Digestion for Inventorying the Snake Venom Arsenal

To improve the characterization of snake venom protein profiles, we report the application of a new generation of proteomic methodology to deeply characterize complex protein mixtures. The new approach, combining a synergic multi-enzymatic and a time-limited digestion (MELD), is a versatile and straightforward protocol previously developed by our group. The higher number of overlapping peptides generated during MELD increases the quality of downstream peptide sequencing and of protein identification. In this context, this work aims at applying the MELD strategy to a venomics purpose for the first time, and especially for the characterization of snake venoms. We used four venoms as the test models for this proof of concept: two Elapidae (Dendroaspis polylepis and Naja naja) and two Viperidae (Bitis arietans and Echis ocellatus). Each venom was reduced and alkylated before being submitted to two different protocols: the classical bottom-up proteomics strategy including a digestion step with trypsin only, or MELD, which combines the activities of trypsin, Glu-C and chymotrypsin with a limited digestion approach. The resulting samples were then injected on an M-Class chromatographic system, and hyphenated to a Q-Exactive Mass Spectrometer. Toxins and protein identification were performed by Peaks Studio X+. The results show that MELD considerably improves the number of sequenced (de novo) peptides and identified peptides from protein databases, leading to the unambiguous identification of a greater number of toxins and proteins. For each venom, MELD was successful, not only in terms of the identification of the major toxins (increasing of sequence coverage), but also concerning the less abundant cellular components (identification of new groups of proteins). In light of these results, MELD represents a credible methodology to be applied as the next generation of proteomics approaches dedicated to venomic analysis. It may open new perspectives for the sequencing and inventorying of the venom arsenal and should expand global knowledge about venom composition.

Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue

Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.

Recent advances in microfluidics for single-cell functional proteomics

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Evaluation of a Pooling Chemoproteomics Strategy with an FDA-Approved Drug Library

Chemoproteomics is a key platform for characterizing the mode of action for compounds, especially for targeted protein degraders such as proteolysis targeting chimeras (PROTACs) and molecular glues. With deep proteome coverage, multiplexed tandem mass tag-mass spectrometry (TMT-MS) can tackle up to 18 samples in a single experiment. Here, we present a pooling strategy for further enhancing the throughput and apply the strategy to an FDA-approved drug library (95 best-in-class compounds). The TMT-MS-based pooling strategy was evaluated in the following steps. First, we demonstrated the capability of TMT-MS by analyzing more than 15 000 unique proteins (> 12 000 gene products) in HEK293 cells treated with five PROTACs (two BRD/BET degraders and three degraders for FAK, ALK, and BTK kinases). We then introduced a rationalized pooling strategy to separate structurally similar compounds in different pools and identified the proteomic response to 14 pools from the drug library. Finally, we validated the proteomic response from one pool by reprofiling the cells via treatment with individual drugs with sufficient replicates. Interestingly, numerous proteins were found to change upon drug treatment, including AMD1, ODC1, PRKX, PRKY, EXO1, AEN, and LRRC58 with 7-hydroxystaurosporine; C6orf64, HMGCR, and RRM2 with Sorafenib; SYS1 and ALAS1 with Venetoclax; and ATF3, CLK1, and CLK4 with Palbocilib. Thus, pooling chemoproteomics screening provides an efficient method for dissecting the molecular targets of compound libraries.

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.

Top-Down Ion Mobility Separations of Isomeric Proteoforms

Continuing advances in proteomics highlight the ubiquity and biological importance of proteoforms─proteins with varied sequence, splicing, or distribution of post-translational modifications (PTMs). The preeminent example is histones, where the PTM pattern encodes the combinatorial language controlling the DNA transcription central to life. While the proteoforms with distinct PTM compositions are distinguishable by mass, the isomers with permuted PTMs commonly coexisting in cells generally require separation before mass-spectrometric (MS) analyses. That was accomplished on the bottom-up and middle-down levels using chromatography or ion mobility spectrometry (IMS), but proteolytic digestion obliterates the crucial PTM connectivity information. Here, we demonstrate baseline IMS resolution of intact isomeric proteoforms, specifically the acetylated H4 histones (11.3 kDa). The proteoforms with a single acetyl moiety on five alternative lysine residues (K5, K8, K12, K16, K20) known for distinct functionalities in vivo were constructed by two-step native chemical ligation and separated using trapped IMS at the resolving power up to 350 on the Bruker TIMS/ToF platform. Full resolution for several pairs was confirmed using binary mixtures and by unique fragments in tandem MS employing collision-induced dissociation. This novel capability for top-down proteoform characterization is poised to open major new avenues in proteomics and epigenetics.

Blue Light Regulates Cell Wall Structure and Carbohydrate Metabolism of Soybean Hypocotyl

Soybean stem elongation and thickening are related to cell wall composition. Plant morphogenesis can be influenced by blue light, which can regulate cell wall structure and composition, and affect stem growth and development. Here, using proteomics and metabolomics, differentially expressed proteins and metabolites of hypocotyls grown in the dark and under blue light were studied to clarify the effects of blue light on the cell wall structure and carbohydrate metabolism pathway of soybean hypocotyls. Results showed that 1120 differential proteins were upregulated and 797 differential proteins were downregulated under blue light treatment, while 63 differential metabolites were upregulated and 36 differential metabolites were downregulated. Blue light promoted the establishment of cell wall structure and composition by regulating the expression of both the enzymes and metabolites related to cell wall structural composition and nonstructural carbohydrates. Thus, under blue light, the cross-sectional area of the hypocotyl and xylem were larger, the longitudinal length of pith cells was smaller, elongation of the soybean hypocotyl was inhibited, and diameter was increased.

Two-CyDye-Based 2D-DIGE Analysis of Aged Human Muscle Biopsy Specimens

The gradual loss of skeletal muscle mass during aging and associated decline in contractile strength can result in reduced fitness, frailty, and loss of independence. In order to better understand the molecular and cellular mechanisms that underlie sarcopenia of old age and the frailty syndrome, as well as identify novel therapeutic targets to treat age-related fiber wasting, it is crucial to develop a comprehensive biomarker signature of muscle aging. Fluorescence two-dimensional gel electrophoresis (2D-DIGE) in combination with sensitive mass spectrometry presents an ideal bioanalytical tool for biomarker discovery in biogerontology. This chapter outlines the application of the 2D-DIGE method for the comparative analysis of human biopsy specimens from middle-aged versus senescent individuals using a two-CyDye-based method.

Capillary liquid chromatography coupled with mass spectrometry for analysis of nanogram protein quantities on a wide-pore superficially porous particle column in top-down proteomics

In top-down proteomics experiments, intact protein ions are subjected to gas-phase fragmentation for MS analysis without prior digestion. This approach is used to characterize post-translational modifications and clipped forms of proteins, avoids several "inference" problems associated with bottom-up proteomics, and is well suited to the study of proteoforms. In the past decade, top-down proteomics has progressed rapidly, taking advantage of MS instrumentation improvements and the efforts of pioneering groups working to improve sample handling and data processing. The potential of this technology has been established through its successful use in a number of important biological studies. However, many challenges remain to be addressed like improving protein separation capabilities such that it might become possible to expand the dynamic range of whole proteome analysis, address co-elution and convoluted mass spectral data, and aid final data processing from peak identification to quantification. In this study, we investigated the use of a wide-pore silica-based superficially porous media with a high coverage phenyl bonding, commercially packed into customized capillary columns for the purpose of top-down proteomics. Protein samples of increasing complexity were tested, namely subunit digests of a monoclonal antibody, components of purified histones and proteins extracted from eukaryotic ribosomes. High quality mass spectra were obtained from only 100 ng of protein sample while using difluoroacetic acid as an ion pairing agent to improve peak shape and chromatographic resolution. A peak width at half height of about 15 s for a 45 min gradient time was observed on a complex mixture giving an estimated peak capacity close to 100. Most importantly, efficient separations were obtained for highly diverse proteins and there was no need to make method specific adjustments, suggesting this is a highly versatile and easy-to-use setup for top-down proteomics.

Integrated top-down and bottom-up proteomics mass spectrometry for the characterization of endogenous ribosomal protein heterogeneity

Ribosomes are abundant, large RNA-protein complexes that are the sites of all protein synthesis in cells. Defects in ribosomal proteins (RPs), including proteoforms arising from genetic variations, alternative splicing of RNA transcripts, post-translational modifications and alterations of protein expression level, have been linked to a diverse range of diseases, including cancer and aging. Comprehensive characterization of ribosomal proteoforms is challenging but important for the discovery of potential disease biomarkers or protein targets. In the present work, using E. coli 70S RPs as an example, we first developed a top-down proteomics approach on a Waters Synapt G2 Si mass spectrometry (MS) system, and then applied it to the HeLa 80S ribosome. The results were complemented by a bottom-up approach. In total, 50 out of 55 RPs were identified using the top-down approach. Among these, more than 30 RPs were found to have their N-terminal methionine removed. Additional modifications such as methylation, acetylation, and hydroxylation were also observed, and the modification sites were identified by bottom-up MS. In a HeLa 80S ribosomal sample, we identified 98 ribosomal proteoforms, among which multiple truncated 80S ribosomal proteoforms were observed, the type of information which is often overlooked by bottom-up experiments. Although their relevance to diseases is not yet known, the integration of top-down and bottom-up proteomics approaches paves the way for the discovery of proteoform-specific disease biomarkers or targets.

Comparative 3-Sample 2D-DIGE Analysis of Skeletal Muscles

The skeletal muscle proteome consists of a large number of diverse protein species with a broad and dynamic concentration range. Since mature skeletal muscles are characterized by a distinctive combination of contractile cells with differing physiological and biochemical properties, it is essential to determine specific differences in the protein composition of fast, slow, and hybrid fibers. Fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) is a powerful comparative tool to analyze fiber type-specific differences between predominantly fast contracting versus slower twitching muscles. In this chapter, the application of the 2D-DIGE method for the comparative analysis of different subtypes of skeletal muscles is outlined in detail. A standardized proteomic workflow is described, involving sample preparation, protein extraction, differential fluorescence labeling using a 3-CyDye system, first-dimension isoelectric focusing, second-dimension slab gel electrophoresis, 2D-DIGE image analysis, protein digestion, and mass spectrometry.

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine

With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics technologies, including bulk and single-cell omics approaches, have empowered to characterize different molecular layers at unprecedented scale and resolution, providing a holistic view of tumor behavior. Multi-omics analysis allows systematic interrogation of various molecular information at each biological layer while posing tricky challenges regarding how to extract valuable insights from the exponentially increasing amount of multi-omics data. Therefore, efficient algorithms are needed to reduce the dimensionality of the data while simultaneously dissecting the mysteries behind the complex biological processes of cancer. Artificial intelligence has demonstrated the ability to analyze complementary multi-modal data streams within the oncology realm. The coincident development of multi-omics technologies and artificial intelligence algorithms has fuelled the development of cancer precision medicine. Here, we present state-of-the-art omics technologies and outline a roadmap of multi-omics integration analysis using an artificial intelligence strategy. The advances made using artificial intelligence-based multi-omics approaches are described, especially concerning early cancer screening, diagnosis, response assessment, and prognosis prediction. Finally, we discuss the challenges faced in multi-omics analysis, along with tentative future trends in this field. With the increasing application of artificial intelligence in multi-omics analysis, we anticipate a shifting paradigm in precision medicine becoming driven by artificial intelligence-based multi-omics technologies.

Bacteriocin Production by Bacillus Species: Isolation, Characterization, and Application

Antibiotic resistance is a problem that has been increasing lately; therefore, it is important to find new alternatives to treat infections induced by pathogens that cannot be eliminated with available products. Small antimicrobial peptides (AMPs) known as bacteriocin could be an alternative to antibiotics because they have shown to be effective against a great number of multidrug-resistant microbes. In addition to its high specificity against microbial pathogens and its low cytotoxicity against human cells, most bacteriocin present tolerance to enzyme degradation and stability to temperature and pH alterations. Bacteriocins are small peptides with a great diversity of structures and functions; however, their mechanisms of action are still not well understood. In this review, bacteriocin produced by Bacillus species will be described, especially its mechanisms of action, culture conditions used to improve its production and state-of-the-art methodologies applied to identify them. Bacteriocin utilization as food preservatives and as new molecules to treat cancer also will be discussed.

Mesowestern Blot: Simultaneous Analysis of Hundreds of Submicroliter Lysates

Western blotting is a widely used technique for molecular-weight-resolved analysis of proteins and their posttranslational modifications, but high-throughput implementations of the standard slab gel arrangement are scarce. The previously developed Microwestern requires a piezoelectric pipetting instrument, which is not available for many labs. Here, we report the Mesowestern blot, which uses a 3D-printable gel casting mold to enable high-throughput Western blotting without piezoelectric pipetting and is compatible with the standard sample preparation and small (∼1 μL) sample sizes. The main tradeoffs are reduced molecular weight resolution and higher sample-to-sample CV, making it suitable for qualitative screening applications. The casted polyacrylamide gel contains 336, ∼0.5 μL micropipette-loadable sample wells arranged within a standard microplate footprint. Polyacrylamide % can be altered to change molecular weight resolution profiles. Proof-of-concept experiments using both infrared-fluorescent molecular weight protein ladder and cell lysate (RIPA buffer) demonstrate that the protein loaded in Mesowestern gels is amenable to the standard Western blotting steps. The main difference between Mesowestern and traditional Western is that semidry horizontal instead of immersed vertical gel electrophoresis is used. The linear range of detection is at least 32-fold, and at least ∼500 attomols of β-actin can be detected (∼29 ng of total protein from mammalian cell lysates: ∼100-300 cells). Because the gel mold is 3D-printable, users with access to additive manufacturing cores have significant design freedom for custom layouts. We expect that the technique could be easily adopted by any typical cell and molecular biology laboratory already performing Western blots.

Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes

ABSTRACT

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide that threatens both maternal and fetal health. Identifying individuals at high risk for GDM and diabetes after GDM is particularly useful for early intervention and prevention of disease progression. In the last decades, a number of studies have used metabolomics, genomics, and proteomic approaches to investigate associations between biomolecules and GDM progression. These studies clearly demonstrate that various biomarkers reflect pathological changes in GDM. The established markers have potential use as screening and diagnostic tools in GDM and in postpartum diabetes research. In the present review, we summarize recent studies of metabolites, single-nucleotide polymorphisms, microRNAs, and proteins associated with GDM and its transition to postpartum diabetes, with a focus on their predictive value in screening and diagnosis.

Proteomic Discovery and Validation of Novel Fluid Biomarkers for Improved Patient Selection and Prediction of Clinical Outcomes in Alzheimer’s Disease Patient Cohorts

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include the buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. There is an urgent need to identify early detection and disease progression biomarkers that can facilitate AD drug development. The current established readouts based on the expression levels of amyloid beta, tau, and phospho-tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, cerebrospinal fluid (CSF), or other biofluids that can facilitate the early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry are now being increasingly applied to study AD disease mechanisms and identify drug targets and novel disease biomarkers. In this report, we describe the application of quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD, and discuss the development and validation of new predictive and diagnostic disease biomarkers.

Protein Adsorption Loss─The Bottleneck of Single-Cell Proteomics

Single-cell proteomics is a promising field to provide direct yet comprehensive molecular insights into cellular functions without averaging effects. Here, we address a grand technical challenge impeding the maturation of single-cell proteomics─protein adsorption loss (PAL). Even though widely known, there is currently no quantitation on how profoundly and selectively PAL has affected single-cell proteomics. Therefore, the mitigations to this challenge have been generic, and their efficacy was only evaluated by the size of the resolved proteome with no specificity on individual proteins. We use the existing knowledge of PAL, protein expression, and the typical surface area used in single-cell proteomics to discuss the severity of protein loss. We also summarize the current solutions to this challenge and briefly review the available methods to characterize the physical and chemical properties of protein surface adsorption. By citing successful strategies in single-cell genomics for measurement errors in individual transcripts, we pinpoint the urgency to benchmark PAL at the proteome scale with individual protein resolution. Finally, orthogonal single-cell proteomic techniques that have the potential to cross validate PAL are proposed. We hope these efforts can promote the fruition of single-cell proteomics in the near future.