Standardization approaches in absolute quantitative proteomics with mass spectrometry

Proteomic Identification of Small Extracellular Vesicle Proteins LAMB1 and Histone H4 for Prostate Cancer Diagnosis and Risk Stratification

Diagnosis and stratification of prostate cancer (PCa) patients using the prostate-specific antigen (PSA) test is challenging. Extracellular vesicles (EVs), as a new star of liquid biopsy, has attracted interest to complement inaccurate PSA screening and invasiveness of tissue biopsy. In this study, a panel of potential small EV (sEV) protein biomarkers is identified from PCa cell lines using label-free LC-MS/MS proteomics. These biomarkers underwent further validation with plasma and urine samples from different PCa stages through parallel reaction monitoring-based targeted proteomics, western blotting, and ELISA. Additionally, a tissue microarray containing cancerous and noncancerous tissues is screened to provide additional evidence of selected sEV proteins associated with cancer origin. Results indicate that sEV protein LAMB1 is highly expressed in human plasma of metastatic PCa patients compared with localised PCa patients and control subjects, while sEV protein Histone H4 is highly expressed in human urine of high-risk PCa patients compared to low-risk PCa patients and control subjects. These two sEV proteins demonstrate higher specificity and sensitivity than the PSA test and show promise for metastatic PCa diagnosis, progression monitoring, and risk stratification.

Absolute quantification methods for Prostate-Specific antigen by Isotope-Dilution mass spectrometry

Prostate-specific antigen (PSA) is a diagnostic marker for prostate cancer; however, because it is a macromolecular glycoprotein with complex and diverse isoforms, it is difficult to standardize clinical PSA detection results. To overcome this limitation, herein, naturally extracted PSA was characterized as free PSA (fPSA), and the PSA solution was successfully quantified by amino acid analysis coupled with isotope-dilution mass spectrometry (AAA-IDMS) and enzymatic hydrolysis-IDMS; the results could be traced to the International System of Units (SI) through absolutely quantified amino acids and peptides. After protein hydrolysis or digestion condition optimization, amino acids and signature peptides were detected by liquid chromatography-mass spectrometry with the multiple reaction monitoring mode. The mass concentrations of PSA obtained through AAA-IDMS and enzymatic hydrolysis-IDMS were (75.3 ± 1.5) µg/g (k = 2) and (74.7 ± 1.7) µg/g (k = 2), respectively. The PSA weighted average mass concentration was (75.0 ± 1.6) µg/g (k = 2). The consistency assessment between the two methods was successfully validated, ensuring absolute quantitative accuracy. This study lays the foundation for the development of high-order reference materials for the clinical detection of PSA, which can improve the accuracy, reliability, and consistency of clinical PSA test results.

Comparative study of the commonly used protein quantitation assays on different Hymenoptera venoms: A fundamental aspect of Hymenoptera venom proteome analysis

Determination of protein concentration in Hymenoptera venoms requires an accurate and reproducible assay as the results will be used to support subsequent proteomic techniques employed in their analyses. However, all protein assay techniques have inherent strengths and weaknesses, demanding their assessment before selecting the most suitable platform for sample analysis. In this study, protein profiles of ant, honeybee, and wasp venoms, and bovine serum albumin (BSA) and hyaluronidase standards were qualitatively assessed using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Their amino acid and protein concentration were quantitatively determined via Amino Acid Analysis (AAA). Amino acid concentration was determined via hydrolysis, derivatization, and chromatographic quantification. Protein concentration was estimated using four different protein concentration assays. The ratios of protein concentration in venom samples to protein standards were calculated, and the accuracy of the protein concentration assays was analysed relative to the concentration determined from AAA. SDS-PAGE analysis showed that BSA contained several protein bands, while hyaluronidase contained a mixture of peptide and protein bands. Ant and honeybee venoms contained a higher proportion of peptide bands, while wasp venom contained more protein bands. As determined by AAA, the ratio of protein concentration in Hymenoptera venoms varied between 1.01 and 1.11 to BSA, and between 0.96 and 1.06 to hyaluronidase. Overall, the Bradford assay was found to be the least accurate and the BCA assay was the most accurate in estimating protein concentration in Hymenoptera venoms. There was no significant advantage in using hyaluronidase as a standard or increasing incubation temperature of BCA assay when analysing Hymenoptera venoms. Diluent solutions containing phenol and human serum albumin interfered with Lowry-based assays.

Protein constraints in genome-scale metabolic models: Data integration, parameter estimation, and prediction of metabolic phenotypes

Genome-scale metabolic models provide a valuable resource to study metabolism and cell physiology. These models are employed with approaches from the constraint-based modeling framework to predict metabolic and physiological phenotypes. The prediction performance of genome-scale metabolic models can be improved by including protein constraints. The resulting protein-constrained models consider data on turnover numbers (kcat ) and facilitate the integration of protein abundances. In this systematic review, we present and discuss the current state-of-the-art regarding the estimation of kinetic parameters used in protein-constrained models. We also highlight how data-driven and constraint-based approaches can aid the estimation of turnover numbers and their usage in improving predictions of cellular phenotypes. Finally, we identify standing challenges in protein-constrained metabolic models and provide a perspective regarding future approaches to improve the predictive performance.

Evaluation of different isotope dilution mass spectrometry strategies for the characterization of naturally abundant and isotopically labelled peptide standards

Natural abundance and isotopically labelled tryptic peptides are routinely employed as standards in quantitative proteomics. The certification of the peptide content is usually carried out by amino acid analysis using isotope dilution mass spectrometry (IDMS) after the acid hydrolysis of the peptide. For the validation and traceability of the amino acid analysis procedure, expensive certified peptides must be employed. In this work we evaluate different IDMS alternatives which will reduce the amount of certified peptide required for validation of the amino acid analysis procedure. In this context, the characterization of both natural and isotopically labelled synthetic angiotensin I peptides was carried out. First, we applied a fast procedure for peptide hydrolysis based on microwave-assisted digestion and employed two certified peptide reference materials SRM 998 angiotensin I and CRM 6901-b C-peptide for validation of the hydrolysis procedure. The amino acids proline, leucine, isoleucine, valine, tyrosine, arginine and phenylalanine were evaluated for their suitability for peptide certification by IDMS by both liquid chromatography with tandem mass spectrometry (LC-MS/MS) and gas chromatography with mass spectrometry (GC)-MS/MS. Then, natural angiotensin I and 13C1-labelled angiotensin I were synthesized in-house and purified by preparative liquid chromatography. The concentration of the 13C1-labelled angiotensin I peptide was established by reverse IDMS in its native form using SRM 998 angiotensin I as reference. The concentration of the natural synthesized peptide was determined by IDMS both using the 13C1-labelled peptide in its native form and by amino acid analysis showing comparable results. Finally, the synthetic naturally abundant angiotensin I peptide was employed as "in-house" standard for the validation of subsequent peptide characterization procedures. Therefore, the novelty of this work relies on, first, the development of a faster hydrolysis procedure assisted by focused microwaves, providing complete hydrolysis in 150 min, and secondly, a validation strategy combining GC-MS and LC-MS/MS that allowed us to certify the purity of an in-house-synthesized peptide standard that can be employed as quality control in further experiments.

Cluster-Enhanced Nanopore Sensing of Ovarian Cancer Marker Peptides in Urine

The development of novel methodologies that can detect biomarkers from cancer or other diseases is both a challenge and a need for clinical applications. This partly motivates efforts related to nanopore-based peptide sensing. Recent work has focused on the use of gold nanoparticles for selective detection of cysteine-containing peptides. Specifically, tiopronin-capped gold nanoparticles, trapped in the cis-side of a wild-type α-hemolysin nanopore, provide a suitable anchor for the attachment of cysteine-containing peptides. It was recently shown that the attachment of these peptides onto a nanoparticle yields unique current signatures that can be used to identify the peptide. In this article, we apply this technique to the detection of ovarian cancer marker peptides ranging in length from 8 to 23 amino acid residues. It is found that sequence variability complicates the detection of low-molecular-weight peptides (<10 amino acid residues), but higher-molecular-weight peptides yield complex, high-frequency current fluctuations. These fluctuations are characterized with chi-squared and autocorrelation analyses that yield significantly improved selectivity when compared to traditional open-pore analysis. We demonstrate that the technique is capable of detecting the only two cysteine-containing peptides from LRG-1, an emerging protein biomarker, that are uniquely present in the urine of ovarian cancer patients. We further demonstrate the detection of one of these LRG-1 peptides spiked into a sample of human female urine.

Quantitative mass spectrometry imaging: therapeutics & biomolecules

Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology.

Special Issue with Research Topics on "Recent Analysis and Applications of Mass Spectra on Biochemistry"

Analytical mass spectrometry applies irreplaceable mass spectrometric (MS) methods to analytical chemistry and chemical analysis, among other areas of analytical science [...].

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Label-free quantification of host cell protein impurity in recombinant hemoglobin materials

Quantitative analysis relies on pure-substance primary calibrators with known mass fractions of impurity. Here, label-free quantification (LFQ) is being evaluated as a readily available, reliable method for determining the mass fraction of host cell proteins (HCPs) in bioengineered proteins which are intended for use as protein calibration standards. In this study a purified hemoglobin-A2 (HbA2) protein, obtained through its overexpression in E. coli, was used. Two different materials were produced: natural and U15N-labeled HbA2. For the quantification of impurities, precursor ion (MS1-) intensities were integrated over all E. coli proteins identified and divided by the intensities obtained for HbA2. This ratio was calibrated against the corresponding results for an E. coli cell lysate, which had been spiked at known mass ratios to pure HbA2. To demonstrate the universal applicability of LFQ, further proteomes (yeast and human K562) were then alternatively used for calibration and found to produce comparable results. Valid results were also obtained when the complexity of the calibrator was reduced to a mix of just nine proteins, and a minimum of five proteins was estimated to be sufficient to keep the sampling error below 15%. For the studied materials, HbA2 mass fractions (or purities) of 923 and 928 mg(HbA2)/g(total protein) were found with expanded uncertainties (U) of 2.8 and 1.3%, resp. Value assignment by LFQ thus contributes up to about 3% of the overall uncertainty of HbA2 quantification when these materials are used as calibrators. Further purification of the natural HbA2 yielded a mass fraction of 999.1 mg/g, with a negligible uncertainty (U = 0.02%), though at a significant loss of material. If an overall uncertainty of 5% is acceptable for protein quantification, working with the original materials would therefore definitely be viable, circumventing the need of further purification.

The role of proteomics in acute pancreatitis: new and old knowledge

INTRODUCTION

Around 20% of individuals diagnosed with acute pancreatitis (AP) may develop severe acute pancreatitis (SAP), possibly resulting in a mortality rate ranging from 15% to 35%. There is an urgent need to thoroughly understand the molecular phenotypes of SAP resulting from diverse etiologies. The field of translational research on AP has seen the use of several innovative proteomic methodologies via the ongoing improvement of isolation, tagging, and quantification methods.

AREAS COVERED

This paper provides a comprehensive overview of differentially abundant proteins (DAPs) identified in AP by searching the PubMed/MEDLINE database (2003-2023) and adds significantly to the current theoretical framework.

EXPERT OPINION

DAPs for potentially diagnosing AP based on proteomic identification need to be confirmed by multi-center studies that include larger samples. The discovery of DAPs in various organs at different AP stages via proteomic technologies is essential better to understand the pathophysiology of AP-related multiple organ dysfunction syndrome. Regarding the translational research of AP, novel approaches like single-cell proteomics and imaging using mass spectrometry may be used as soon as they become available.

Epidemiological investigation and proteomic profiling of typical TCM syndrome in HIV/AIDS immunological nonresponders

HIV/AIDS pandemic remains the world's most severe public health challenge, especially for HIV/AIDS immunological nonresponders (HIV/AIDS-INRs), who tend to have higher mortality. Due to the advantages in promoting patients' immune reconstitution, Traditional Chinese medicine (TCM) has become one of the mainstays of complementary treatments for HIV/AIDS-INRs. Given that effective TCM treatments largely depend on precise syndrome differentiation, there is an increasing interest in exploring biological evidence for the classification of TCM syndromes in HIV/AIDS-INRs. In our study, to identify the typical HIV/AIDS-INRs syndrome, an epidemiological survey was first conducted in the Liangshan prefecture (China), a high HIV/AIDS prevalence region. The key TCM syndrome, Yang deficiency of spleen and kidney (YDSK), was evaluated by using a tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS). A total of 62 differentially expressed proteins (DEPs) of YDSK syndrome compared with healthy people were screened out. Comparative bioinformatics analyses showed that DEPs in YDSK syndrome were mainly associated with response to wounding and acute inflammatory response in the biological process. The pathway annotation is mainly enriched in complement and coagulation cascades. Finally, the YDSK syndrome-specific DEPs such as HP and S100A9 were verified by ELISA, and confirmed as potential biomarkers for YDSK syndrome. Our study may lay the biological and scientific basis for the specificity of TCM syndromes in HIV/AIDs-INRs, and may provide more opportunities for the deep understanding of TCM syndromes and the developing more effective and stable TCM treatment for HIV/AIDS-INRs.

Accurate prediction of in vivo protein abundances by coupling constraint-based modelling and machine learning

Quantification of how different environmental cues affect protein allocation can provide important insights for understanding cell physiology. While absolute quantification of proteins can be obtained by resource-intensive mass-spectrometry-based technologies, prediction of protein abundances offers another way to obtain insights into protein allocation. Here we present CAMEL, a framework that couples constraint-based modelling with machine learning to predict protein abundance for any environmental condition. This is achieved by building machine learning models that leverage static features, derived from protein sequences, and condition-dependent features predicted from protein-constrained metabolic models. Our findings demonstrate that CAMEL results in excellent prediction of protein allocation in E. coli (average Pearson correlation of at least 0.9), and moderate performance in S. cerevisiae (average Pearson correlation of at least 0.5). Therefore, CAMEL outperformed contending approaches without using molecular read-outs from unseen conditions and provides a valuable tool for using protein allocation in biotechnological applications.

PARROT: Prediction of enzyme abundances using protein-constrained metabolic models

Protein allocation determines the activity of cellular pathways and affects growth across all organisms. Therefore, different experimental and machine learning approaches have been developed to quantify and predict protein abundance and how they are allocated to different cellular functions, respectively. Yet, despite advances in protein quantification, it remains challenging to predict condition-specific allocation of enzymes in metabolic networks. Here, using protein-constrained metabolic models, we propose a family of constrained-based approaches, termed PARROT, to predict how much of each enzyme is used based on the principle of minimizing the difference between a reference and an alternative growth condition. To this end, PARROT variants model the minimization of enzyme reallocation using four different (combinations of) distance functions. We demonstrate that the PARROT variant that minimizes the Manhattan distance between the enzyme allocation of a reference and an alternative condition outperforms existing approaches based on the parsimonious distribution of fluxes or enzymes for both Escherichia coli and Saccharomyces cerevisiae. Further, we show that the combined minimization of flux and enzyme allocation adjustment leads to inconsistent predictions. Together, our findings indicate that minimization of protein allocation rather than flux redistribution is a governing principle determining steady-state pathway activity for microorganism grown in alternative growth conditions.

Proteomic analysis reveals oxidative stress-induced activation of Hippo signaling in thiamethoxam-exposed Drosophila

Thiamethoxam (THIA) is a widely used neonicotinoid insecticide. However, the toxicity and defense mechanisms activated in THIA-exposed insects are unclear. Here, we used isobaric tags for relative and absolute quantitation (iTRAQ) proteomics technology to identify changes in protein expression in THIA-exposed Drosophila. We found that the antioxidant proteins Cyp6a23 and Dys were upregulated, whereas vir-1 was downregulated, which may have been detoxification in response to THIA exposure. Prx5 downregulation promoted the generation of reactive oxygen species. Furthermore, the accumulation of reactive oxygen species led to the induction of antioxidant defenses in THIA-exposed Drosophila, thereby enhancing the levels of oxidative stress markers (e.g., superoxide dismutase, glutathione S-transferase, and glutathione) and reducing catalase expression. Furthermore, the Hippo signaling transcription coactivator Yki was inactivated by THIA. Our results suggesting that Hippo signaling may be necessary to promote insect survival in response to neonicotinoid insecticide toxicity.

Harmonization and standardization of biofluid-based biomarker measurements for AT(N) classification in Alzheimer's disease

Fluid biomarkers are currently measured in cerebrospinal fluid and blood for Alzheimer's disease diagnosis and are promising targets for drug development and for patients' follow-up in clinical trials. These biomarkers have been grouped in an unbiased research framework, the amyloid (Aβ), tau, and neurodegeneration (AT[N]) biomarker system to aid patients' early diagnosis and stratification. Metrological approaches relying on mass spectrometry have been used for the development of reference materials and reference measurement procedures. Despite their excellent performances as clinical tools, fluid biomarkers often present an important between-laboratory variation. Standardization efforts were carried out on the biomarkers currently included in the AT(N) classification system, involving the collaboration of national metrology institutes, clinicians, researchers, and in vitro diagnostic providers. This article provides an overview of current activities towards standardization. These reference methods and reference materials may be used for recalibration of immunoassays and the establishment of standardized cutoff values allowing a better stratification of Alzheimer's disease patients.

Highlights

The AT(N) biomarker system allows stratifying AD patients on the basis of biomarker profiles.Fluid biomarker measurements often present an important between-laboratory variation preventing the establishment of standardized cutoff values.Overview on the standardization initiatives involving the fluid biomarkers currently included in the AT(N) framework.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Certification of protein biomarker standards using element MS and generic standards: Application to human cytokines

The availability of protein standards and methods for their characterization, quantification, and purity assessment are currently a bottleneck in absolute quantitative proteomics. In this work, we introduce an absolute quantitative analytical strategy based on ICP-MS sulfur detection that uses sulfate as generic standard to quantify and certify the mass purity of protein standards. The methodology combines capillary chromatographic separation with parallel detection with ICP-MS and ESI-MS to determine proteoforms concentration and identity, respectively. The workability of the methodology was demonstrated using recombinant human cytokine standards IP-10 and Flt3L (2 batches), which are relevant biomarkers for carcinoma or inflammatory diseases. Every key factor (transport efficiency, column recovery, signal stability and internal standard suitability) was taken into account and certified BSA standard was used as quality control for validation purposes. Protein quantification values and resulting mass purity certification of IP-10 and one batch of Flt3L were very high (100 and 86%, respectively). Lower mass purity obtained for another batch of Flt3L (<70%) concurred with the finding of significant proteoforms resulted from oxidation processes as observed by parallel ESI-MS.

The Potential of ICP-MS as a Complementary Tool in Nanoparticle-Protein Corona Analysis

The prolific applicability of nanomaterials has made them a common citizen in biological systems, where they interact with proteins forming a biological corona complex. These complexes drive the interaction of nanomaterials with and within the cells, bringing forward numerous potential applications in nanobiomedicine, but also arising toxicological issues and concerns. Proper characterization of the protein corona complex is a great challenge typically handled with the combination of several techniques. Surprisingly, despite inductively coupled plasma mass spectrometry (ICP-MS) being a powerful quantitative technique whose application in nanomaterials characterization and quantification has been consolidated in the last decade, its application to nanoparticle-protein corona studies is scarce. Furthermore, in the last decades, ICP-MS has experienced a turning point in its capabilities for protein quantification through sulfur detection, hence becoming a generic quantitative detector. In this regard, we would like to introduce the potential of ICP-MS in the nanoparticle protein corona complex characterization and quantification complementary to current methods and protocols.

Novel 15N Metabolic Labeling-Based Large-Scale Absolute Quantitative Proteomics Method for Corynebacterium glutamicum

With fast growth, synthetic biology powers us with the capability to produce high commercial value products in an efficient resource/energy-consuming manner. Comprehensive knowledge of the protein regulatory network of a bacterial host chassis, e.g., the actual amount of the given proteins, is the key to building cell factories for certain target hyperproduction. Many talent methods have been introduced for absolute quantitative proteomics. However, for most cases, a set of reference peptides with isotopic labeling (e.g., SIL, AQUA, QconCAT) or a set of reference proteins (e.g., commercial UPS2 kit) needs to be prepared. The higher cost hinders these methods for large sample research. In this work, we proposed a novel metabolic labeling-based absolute quantification approach (termed nMAQ). The reference Corynebacterium glutamicum strain is metabolically labeled with ¹⁵N, and a set of endogenous anchor proteins of the reference proteome is quantified by chemically synthesized light (¹⁴N) peptides. The prequantified reference proteome was then utilized as an internal standard (IS) and spiked into the target (¹⁴N) samples. SWATH-MS analysis is performed to obtain the absolute expression levels of the proteins from the target cells. The cost for nMAQ is estimated to be less than 10 dollars per sample. We have benchmarked the quantitative performance of the novel method. We believe this method will help with the deep understanding of the intrinsic regulatory mechanism of C. glutamicum during bioengineering and will promote the process of building cell factories for synthetic biology.

Protocol for absolute quantification of proteins in Gram-negative bacteria based on QconCAT-based labeled peptides

Mass-spectrometry-based absolute protein quantification uses labeled quantification concatamer (QconCAT) as internal standards (ISs). To calculate the amount of protein(s), the ion intensity ratio between the analyte and its cognate IS is compared in each biological sample. The present protocol describes a systematic workflow to design, produce, and purify QconCATs and to quantify soluble proteins in Pseudomonas putida KT2440. Our methodology enables the quantification of detectable peptide and serves as a versatile platform to produce ISs for different biological systems.

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

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

Protective effect of Xingnaojing injection on ferroptosis after cerebral ischemia injury in MCAO rats and SH-SY5Y cells

ETHNOPHARMACOLOGICAL RELEVANCE

Xingnaojing（XNJ）injection is a traditional Chinese medicine injection with neuroprotective effect, which has been widely used in the treatment of stroke for many years.

AIM OF THE STUDY

This study aimed to explore the potential mechanism of XNJ in cerebral ischemia mediated by ferroptosis using proteomics and in vivo and in vitro experiments.

MATERIALS AND METHODS

After the rat model of middle cerebral artery occlusion (MCAO) was successfully established, they were randomly divided into model, XNJ, and deferoxamine (DFO) group. Triphenyl tetrazolium chloride (TTC) staining, Hematoxylin and eosin (H&E), and Nissl staining were used to observe the infarct area, pathological changes and the degree of neuronal apoptosis of rat brain. Proteins extracted from rat brain tissues were analyzed by quantitative proteomics using tandem mass tags (TMT). Western blotting and immunohistochemical assessment were used to measure the expression of ferroptosis-related proteins. In vitro, the SH-SY5Y cells were subjected to hypoxia (37°C/5% CO2/1% O2) for 24 h to observe the survival rate, and detect the reactive oxygen species (ROS) content and ferroptosis-related proteins.

RESULTS

In TTC and H&E experiments, we found that XNJ drug treatment reduced the infarct volume and brain tissue damage in MCAO rats. Nissl staining also showed that compared with MCAO group rats, the Nissl bodies of brain tissue after XNJ drug intervention were clear with a 3.54-fold increased times, suggesting that XNJ improved cerebral infraction, and neurological deficits in MCAO rats. Proteomics identified 101 intersected differentially expressed proteins (DEPs). According to the bioinformatics analysis, these DEPs were closely related to ferroptosis. Further research indicated that MCAO-induced cerebral ischemia was alleviated by upregulating recombinant glutathione peroxidase 4 (GPX4), ferroportin (FPN) expression, Heme oxygenase-1 (HO-1) expression, and downregulating cyclooxygenase-2 (COX-2), transferring receptor (TFR) and divalent metal transporter-1 (DMT1) expression after XNJ treatment. In addition, in vitro experiment indicated that XNJ improved the survival rate of hypoxia-damaged SH-SY5Y cells. XNJ increased the level of GPX4 and inhibited the protein expression of COX-2 and TFR after cell hypoxia. Moreover, different concentrations of XNJ (0.25%, 0.5%, 1%) reduced the ROS content of hypoxic cells, suggesting that XNJ could inhibit hypoxia-induced cell damage by regulating the expression of ferroptosis-related proteins and decreasing the production of ROS.

CONCLUSIONS

XNJ could promote the recovery of neurological function in MCAO rats and hypoxia SH-SY5Y cells by regulating ferroptosis.

Review: Advances in the Accuracy and Traceability of Metalloprotein Measurements Using Isotope Dilution Inductively Coupled Plasma Mass Spectrometry

Advances in inductively coupled plasma mass spectrometry and the methods used to prepare isotopically enriched standards, allow for the high accuracy measurement of metalloproteins by isotope dilution mass spectrometry. This technique has now reached a level of maturity whereby a step change in the accuracy, precision, and traceability of, in particular, clinical, and biomedical measurements is achievable. Current clinical measurements, which require low limits of detection in the presence of complex sample matrices, use indirect methods based on immunochemistry for the study of human disease. However, this approach suffers from poor traceability, requiring comparisons based on provision of matrix-based reference materials, used as analytical standards. This leads to difficulty when changes in the reference material are required, often resulting in a lack of interlaboratory and temporal comparability in clinical results and reference ranges. In this review, we focus on the most important metalloproteins for clinical studies, to illustrate how the attributes of chromatography coupled to inorganic mass spectrometry can be used for the direct measurement of metalloproteins such as hemoglobin, transferrin, and ceruloplasmin. By using this approach, we hope to demonstrate how isotope dilution analysis can be used as a reference method to improve traceability and underpin clinical, biomedical, and other biological measurements.

Analysis of Peptide Hormone Maturation and Processing Specificity Using Isotope-Labeled Peptides

Many peptide hormones and growth factors in plants, particularly the small posttranslationally modified signaling peptides, are synthesized as larger precursor proteins. Proteolytic processing is thus required for peptide maturation, and additional posttranslational modifications may contribute to bioactivity. To what extent these posttranslational modifications impact on processing is largely unknown. Likewise, it is poorly understood how the cleavage sites within peptide precursors are selected by specific processing proteases, and whether or not posttranslational modifications contribute to cleavage site recognition. Here, we describe a mass spectrometry-based approach to address these questions. We developed a method using heavy isotope labeling to directly compare cleavage efficiency of different precursor-derived synthetic peptides by mass spectrometry. Thereby, we can analyze the effect of posttranslational modifications on processing and the specific sequence requirements of the processing proteases. As an example, we describe how this method has been used to assess the relevance of tyrosine sulfation for the processing of the Arabidopsis CIF4 precursor by the subtilase SBT5.4.

A community resource to mass explore the wheat grain proteome and its application to the late-maturity alpha-amylase (LMA) problem

BACKGROUND

Late-maturity alpha-amylase (LMA) is a wheat genetic defect causing the synthesis of high isoelectric point alpha-amylase following a temperature shock during mid-grain development or prolonged cold throughout grain development, both leading to starch degradation. While the physiology is well understood, the biochemical mechanisms involved in grain LMA response remain unclear. We have applied high-throughput proteomics to 4,061 wheat flours displaying a range of LMA activities. Using an array of statistical analyses to select LMA-responsive biomarkers, we have mined them using a suite of tools applicable to wheat proteins.

RESULTS

We observed that LMA-affected grains activated their primary metabolisms such as glycolysis and gluconeogenesis; TCA cycle, along with DNA- and RNA- binding mechanisms; and protein translation. This logically transitioned to protein folding activities driven by chaperones and protein disulfide isomerase, as well as protein assembly via dimerisation and complexing. The secondary metabolism was also mobilized with the upregulation of phytohormones and chemical and defence responses. LMA further invoked cellular structures, including ribosomes, microtubules, and chromatin. Finally, and unsurprisingly, LMA expression greatly impacted grain storage proteins, as well as starch and other carbohydrates, with the upregulation of alpha-gliadins and starch metabolism, whereas LMW glutenin, stachyose, sucrose, UDP-galactose, and UDP-glucose were downregulated.

CONCLUSIONS

To our knowledge, this is not only the first proteomics study tackling the wheat LMA issue but also the largest plant-based proteomics study published to date. Logistics, technicalities, requirements, and bottlenecks of such an ambitious large-scale high-throughput proteomics experiment along with the challenges associated with big data analyses are discussed.

Advancement in Analytical Techniques for Determining the Activity of β-Site Amyloid Precursor Protein Cleaving Enzyme 1

Alzheimer's disease (AD) is a degenerative disease of the central nervous system. The pathogenesis is still not fully clear. One of the main histopathological manifestations is senile plaques formed by β-amyloid (Aβ) accumulation. Aβ is generated from the sequential proteolysis of amyloid precursor protein (APP) by β-secretase [i.e. β-site APP cleaving enzyme 1 (BACE1)] and γ-secretase, with a rate-limiting step controlled by BACE1 activity. Therefore, inhibiting BACE1 activity has become a potential therapeutic strategy for AD. The development of reliable detection methods for BACE1 activity plays an important role in early diagnosis of AD and evaluation of the therapeutic effect of new drugs for AD. This article has reviewed the recent advances in BACE1 activity detection techniques. The challenges of applying these analysis techniques to early clinical diagnosis of AD and development trends of the detection techniques have been prospected.

Simultaneous enrichment and sequential separation of glycopeptides and phosphopeptides with poly-histidine functionalized microspheres

Protein phosphorylation and glycosylation coordinately regulate numerous complex biological processes. However, the main methods to simultaneously enrich them are based on the coordination interactions or Lewis acid-base interactions, which suffer from low coverage of target molecules due to strong intermolecular interactions. Here, we constructed a poly-histidine modified silica (SiO₂@Poly-His) microspheres-based method for the simultaneous enrichment, sequential elution and analysis of phosphopeptides and glycopeptides. The SiO₂@Poly-His microspheres driven by hydrophilic interactions and multiple hydrogen bonding interactions exhibited high selectivity and coverage for simultaneous enrichment of phosphopeptides and glycopeptides from 1,000 molar folds of bovine serum albumin interference. Furthermore, “on-line deglycosylation” strategy allows sequential elution of phosphopeptides and glycopeptides, protecting phosphopeptides from hydrolysis during deglycosylation and improving the coverage of phosphopeptides. The application of our established method to HT29 cell lysates resulted in a total of 1,601 identified glycopeptides and 694 identified phosphopeptides, which were 1.2-fold and 1.5-fold higher than those obtained from the co-elution strategy, respectively. The SiO₂@Poly-His based simultaneous enrichment and sequential separation strategy might have great potential in co-analysis of PTMs-proteomics of biological and clinic samples.

Environment-specificity and universality of the microbial growth law

As the nutrient quality changes, the fractions of ribosomal proteins in the proteome are usually positively correlated with the growth rates due to the auto-catalytic nature of ribosomes. While this growth law is observed across multiple organisms, the relation between the ribosome fraction and growth rate is often more complex than linear, beyond models assuming a constant translation speed. Here, we propose a general framework of protein synthesis considering heterogeneous translation speeds and protein degradations. We demonstrate that the growth law curves are generally environment-specific, e.g., depending on the correlation between the translation speeds and ribosome allocations among proteins. Our predictions of ribosome fractions agree quantitatively with data of Saccharomyces cerevisiae. Interestingly, we find that the growth law curve of Escherichia coli nevertheless appears universal, which we prove must exhibit an upward bending in slow-growth conditions, in agreement with experiments. Our work provides insights on the connection between the heterogeneity among genes and the environment-specificity of cell behaviors.

Surrogate peptide selection and internal standardization for accurate quantification of endogenous proteins

Relative quantification techniques have dominated the field of proteomics. However, biomarker discovery, mathematical model development and studies on transporter-mediated drug disposition still need absolute quantification of proteins. The quality of data of trace-level protein quantification is solely dependent on the specific selection of surrogate peptides. Selection of surrogate peptides has a major impact on the accuracy of the method. In this article, the advanced approaches for selection of surrogate peptides, which can provide absolute quantification of the proteins are discussed. In addition, internal standardization, which accounts for variations in the quantitation process to achieve absolute protein quantification is discussed.

Determination of the Time since Deposition of Blood Traces Utilizing a Liquid Chromatography-Mass Spectrometry-Based Proteomics Approach

Knowledge about when a bloodstain was deposited at a crime scene can be of critical value in forensic investigation. A donor of a genetically identified bloodstain could be linked to a suspected time frame and the crime scene itself. Determination of the time since deposition (TsD) has been extensively studied before but has yet to reach maturity. We therefore conducted a proof-of-principle study to study time- and storage-dependent changes of the proteomes of dried blood stains. A bottom-up proteomics approach was employed, and high-resolution liquid-chromatography-mass-spectrometry (HR-LC-MS) and data-independent acquisition (DIA) were used to analyze samples aged over a 2 month period and two different storage conditions. In multivariate analysis, samples showed distinct clustering according to their TsD in both principal component analysis (PCA) and in partial least square discriminant analysis (PLS DA). The storage condition alters sample aging and yields different separation-driving peptides in hierarchical clustering and in TsD marker peptide selection. Certain peptides and amino acid modifications were identified and further assessed for their applicability in assessing passed TsD. A prediction model based on data resampling (Jackknife) was applied, and prediction values for selected peptide ratios were created. Depending on storage conditions and actual sample age, mean prediction performances ranges in between 70 and 130% for the majority of peptides and time points. This places this study as a first in investigating LC-MS based bottom-up proteomics approaches for TsD determination.

FastCAT Accelerates Absolute Quantification of Proteins Using Multiple Short Nonpurified Chimeric Standards

Absolute (molar) quantification of clinically relevant proteins determines their reference values in liquid and solid biopsies. The FastCAT (for Fast-track QconCAT) method employs multiple short (<50 kDa), stable-isotope labeled chimeric proteins (CPs) composed of concatenated quantotypic (Q)-peptides representing the quantified proteins. Each CP also comprises scrambled sequences of reference (R)-peptides that relate its abundance to a single protein standard (bovine serum albumin, BSA). FastCAT not only alleviates the need to purify CP or use sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) but also improves the accuracy, precision, and dynamic range of the absolute quantification by grouping Q-peptides according to the expected abundance of the target proteins. We benchmarked FastCAT against the reference method of MS Western and tested it in the direct molar quantification of neurological markers in human cerebrospinal fluid at the low ng/mL level.

Targeted proteomics for cancer biomarker verification and validation

Targeted proteomics is a method that measures the amount of target proteins via liquid chromatography-tandem mass spectrometry and is used to verify and validate the candidate cancer biomarker proteins. Compared with antibody-based quantification methods such as ELISA, targeted proteomics enables rapid method development, simultaneous measurement of multiple proteins, and high-specificity detection of modifications. Moreover, by spiking the internal standard peptide, targeted proteomics detects the absolute amounts of marker proteins, which is essential for determining the cut-off values for diagnosis and thus for multi-institutional validation. With these unique features, targeted proteomics can seamlessly transfer cancer biomarker candidate proteins from the discovery phase to the verification and validation phases, thereby resulting in an accelerated cancer biomarker pipeline. Furthermore, understanding the basic principles, advantages, and disadvantages is necessary to effectively utilize targeted proteomics in cancer biomarker pipelines. This review aimed to introduce the technical principles of targeted proteomics for cancer biomarker verification and validation.

Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum

Microbes that can recycle one-carbon (C₁) greenhouse gases into fuels and chemicals are vital for the biosustainability of future industries. Acetogens are the most efficient known microbes for fixing carbon oxides CO₂ and CO. Understanding proteome allocation is important for metabolic engineering as it dictates metabolic fitness. Here, we use absolute proteomics to quantify intracellular concentrations for >1,000 proteins in the model acetogen Clostridium autoethanogenum grown autotrophically on three gas mixtures (CO, CO+H₂, or CO+CO₂+H₂). We detect the prioritization of proteome allocation for C₁ fixation and the significant expression of proteins involved in the production of acetate and ethanol as well as proteins with unclear functions. The data also revealed which isoenzymes are likely relevant in vivo for CO oxidation, H₂ metabolism, and ethanol production. The integration of proteomic and metabolic flux data demonstrated that enzymes catalyze high fluxes with high concentrations and high in vivo catalytic rates. We show that flux adjustments were dominantly accompanied by changing enzyme catalytic rates rather than concentrations.

IMPORTANCE Acetogen bacteria are important for maintaining biosustainability as they can recycle gaseous C₁ waste feedstocks (e.g., industrial waste gases and syngas from gasified biomass or municipal solid waste) into fuels and chemicals. Notably, the acetogen Clostridium autoethanogenum is being used as a cell factory in industrial-scale gas fermentation. Here, we perform reliable absolute proteome quantification for the first time in an acetogen. This is important as our work advances both rational metabolic engineering of acetogen cell factories and accurate in silico reconstruction of their phenotypes. Furthermore, this absolute proteomics data set serves as a reference toward a better systems-level understanding of the ancient metabolism of acetogens.

Label-Free LC-MS/MS Analysis Reveals Different Proteomic Profiles between Egg Yolks of Silky Fowl and Ordinary Chickens

The proteomic profiles of Silky fowl egg yolk (SFEY) and Leghorn egg yolk (LEY) were analyzed by bottom-up label-free liquid chromatography–tandem mass spectrometry (LC-MS/MS). From a total of 186 identified proteins, 26 proteins were found significantly differentially abundant between two yolks, of which, 19 were up-regulated and 7 were down-regulated in SFEY, particularly, vitelline membrane outer layer protein 1, transthyretin and ovoinhibitor were up-regulated by 26, 25, and 16 times, respectively. In addition, there were 57 and 6 unique proteins in SFEY and LEY, respectively. Gene Ontology (GO) revealed SFEY contained relatively more abundant protease inhibitors and coagulation-related proteins. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed differentially abundant proteins in SFEY may be actively involved in the regulation of the neuroactive ligand–receptor interaction pathway. This study provides a theoretical basis for the understanding of proteomic and biological differences between these two yolks and can guide for further exploration of nutritional and biomedical use of Silky fowl egg.

Procedure providing SI-traceable results for the calibration of protein standards by sulfur determination and its application on tau

Quantitative proteomics is a growing research area and one of the most important tools in the life sciences. Well-characterized and quantified protein standards are needed to achieve accurate and reliable results. However, only a limited number of sufficiently characterized protein standards are currently available. To fill this gap, a method for traceable protein quantification using sulfur isotope dilution inductively coupled plasma mass spectrometry (ICP-MS) was developed in this study. Gel filtration and membrane filtration were tested for the separation of non-protein-bound sulfur in the protein solution. Membrane filtration demonstrated a better performance due to the lower workload and the very low sulfur blanks of 11 ng, making it well suited for high-purity proteins such as NIST SRM 927, a bovine serum albumin (BSA). The method development was accomplished with NIST SRM 927e and a commercial avidin. The quantified mass fraction of NIST SRM 927e agreed very well with the certified value and showed similar uncertainties (3.6%) as established methods while requiring less sample preparation and no species-specific standards. Finally, the developed procedure was applied to the tau protein, which is a biomarker for a group of neurodegenerative diseases denoted “tauopathies” including, e.g., Alzheimer’s disease and frontotemporal dementia. For the absolute quantification of tau in the brain of transgenic mice overexpressing human tau, a well-defined calibration standard was needed. Therefore, a pure tau solution was quantified, yielding a protein mass fraction of (0.328 ± 0.036) g/kg, which was confirmed by amino acid analysis.

Clinical identification of expressed proteins in adrenal medullary hyperplasia detected with hypertension

BACKGROUND

Hypertension remains a challenging public health problem worldwide, and adrenal gland-related diseases are one class of the major causes for secondary hypertension. Among them, one relatively rare pattern is adrenal hyperplastic hypertension caused by adrenal medullary hyperplasia (AMH), leading to excessive secretion of autonomic catecholamine. Given that the pathological changes of adrenal medulla are not well correlated to the onset and even severity of secondary hypertension, the molecular basis why some AMH patients are accompanied with hypertension remains unclear and is worth exploring.

AIMS

For this reason, this study aims at investigating differentially expressed proteins in clinical AMH tissue, with special focus on the potential contribution of these differentially expressed proteins to AMH development, in order to have a better understanding of mechanisms how AMH leads to secondary hypertension to some extent.

METHODS AND RESULTS

To this end, AMH specimens were successfully obtained and verified through computed tomography (CT) and haematoxylin-eosin (HE) staining. Proteomic analyses of AMH and control tissues revealed 782 kinds of differentially expressed proteins. Compared with the control tissue, there were 357 types of upregulated proteins and 425 types of downregulated proteins detected in AMH tissue. Of interest, these differentially expressed proteins were significantly enriched in 60 gene ontology terms (P < 0.05), including 28 biological process terms, 14 molecular function terms, and 18 cellular component terms. Pathway analysis further indicated that 306 proteins exert their functions in at least one Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Western blotting showed enhanced expression of phenylethanolamine N- methyltransferase (PNMT), myelin protein zero (MPZ), and Ras-related protein Rab-3C (RAB3C), and reduced expression of cluster of differentiation 36 (CD36) observed in AMH tissue in comparison with controls.

CONCLUSIONS

Clinical AMH specimens display a different proteomic profile compared to control tissue. Of note, PNMT, MPZ, RAB3C, and CD36 are found to differentially expressed and can be potential targets for AMH, providing a theoretical basis for mechanistic exploration of AMH along with hypertension.

Median-Based Absolute Quantification of Proteins Using Fully Unlabeled Generic Internal Standard (FUGIS)

By reporting the molar abundance of proteins, absolute quantification determines their stoichiometry in complexes, pathways, or networks. Typically, absolute quantification relies either on protein-specific isotopically labeled peptide standards or on a semiempirical calibration against the average abundance of peptides chosen from arbitrarily selected proteins. In contrast, a generic protein standard FUGIS (fully unlabeled generic internal standard) requires no isotopic labeling, chemical synthesis, or external calibration and is applicable to quantifying proteins of any organismal origin. The median intensity of the peptide peaks produced by the tryptic digestion of FUGIS is used as a single-point calibrant to determine the molar abundance of any codigested protein. Powered by FUGIS, median-based absolute quantification (MBAQ) outperformed other methods of untargeted proteome-wide absolute quantification.

The first central precocious puberty proteomic profiles revealed multiple metabolic networks and novel key disease-associated proteins

Though central precocious puberty (CPP) as a disease that seriously affects the development of a child is increasing year by year, treatment options remain limited and is the same as the 1980s’ method. These are mainly due to the complex pathogenesis of central precocious puberty. Therefore, systems biology approach to identify and explore the multiple factors related to the pathogenesis of central precocious puberty is necessary. Our data established the first proteome profile of CPP revealed 163 down-regulated and 129 were up-regulated differentially expressed proteins. These altered proteins were primarily enriched in three metabolic process including energy metabolism, amino acid metabolism and nitrogenous base metabolism. The identified altered members of the metabolic signaling are valuable and potential novel therapeutic targets of central precocious puberty.

Combined Molecular and Elemental Mass Spectrometry Approaches for Absolute Quantification of Proteomes: Application to the Venomics Characterization of the Two Species of Desert Black Cobras, Walterinnesia aegyptia and Walterinnesia morgani

We report a novel hybrid, molecular and elemental mass spectrometry (MS) setup for the absolute quantification of snake venom proteomes shown here for two desert black cobra species within the genus Walterinnesia, Walterinnesia aegyptia and Walterinnesia morgani. The experimental design includes the decomplexation of the venom samples by reverse-phase chromatography independently coupled to four mass spectrometry systems: the combined bottom-up and top-down molecular MS for protein identification and a parallel reverse-phase microbore high-performance liquid chromatograph (RP-μHPLC) on-line to inductively coupled plasma (ICP-MS/MS) elemental mass spectrometry and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QToF MS). This allows to continuously record the absolute sulfur concentration throughout the chromatogram and assign it to the parent venom proteins separated in the RP-μHPLC-ESI-QToF parallel run via mass profiling. The results provide a locus-resolved and quantitative insight into the three desert black cobra venom proteome samples. They also validate the units of measure of our snake venomics strategy for the relative quantification of snake venom proteomes as % of total venom peptide bonds as a proxy for the % by weight of the venom toxins/toxin families. In a more general context, our work may pave the way for broader applications of hybrid elemental/molecular MS setups in diverse areas of proteomics.

The Arabidopsis PeptideAtlas: Harnessing worldwide proteomics data to create a comprehensive community proteomics resource

We developed a resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis thaliana proteome, such as the significance of protein splice forms and post-translational modifications (PTMs), or simply to obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) data collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical, and biological metadata. Nearly 40 million out of ∼143 million MS/MS (tandem MS) spectra were matched to the reference genome Araport11, identifying ∼0.5 million unique peptides and 17,858 uniquely identified proteins (only isoform per gene) at the highest confidence level (false discovery rate 0.0004; 2 non-nested peptides ≥9 amino acid each), assigned canonical proteins, and 3,543 lower-confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified that were generated from pseudogenes, alternative start, stops, and/or splice variants, and small Open Reading Frames; these features should be considered when updating the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB, and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS/MS data.

Human bronchial-pulmonary proteomics in coronavirus disease 2019 (COVID-19) pandemic: applications and implications

INTRODUCTION

The outbreak of the newly discovered human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has disrupted the normal life of almost every civilization worldwide. Studies have shown that the coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 can affect multiple human organs and physiological systems, but the respiratory system remains the primary location for viral infection.

AREAS COVERED

We summarize how omics technologies are used in SARS-CoV-2 research and specifically review the current knowledge of COVID-19 from the aspect of human bronchial-pulmonary proteomics. Also, knowledge gaps in COVID-19 that can be fulfilled by proteomics are discussed.

EXPERT OPINION

Overall, human bronchial-pulmonary proteomics plays an important role in revealing the dynamics, functions, tropism, and pathogenicity of SARS-CoV-2, which is crucial for COVID-19 biomarker and therapeutic target discoveries. To more fully understand the impact of COVID-19, research from various angles using multi-omics approaches should also be conducted on the lungs as well as other organs.

Complement multiplex testing: Concept, promises and pitfalls

Complement is a complex system. This complexity becomes more obvious when looking at complement analysis in health and disease, where one presentation can require a number of measurements to understand the full role of this cascade in the disease. The current state of clinical testing requires multiple tests to cover the whole of the complement cascade. There is a clear potential for multiplex testing to help address this need for comprehensive analysis of the state of complement deficiency, activation or inhibition. Fortunately, there are a number of potential methods for multiplex analysis, each with advantages and disadvantages that need to be considered in light of the intricacy of the complement cascade and its interconnection to other systems. Despite the complexities of such methods several groups have started utilizing multiplex analysis for research and even for diagnostic testing. The potential methods, current successes, and the type of testing that needs to be streamlined are reviewed in this text.

Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.

Mass Spectrometry Provides a Highly Sensitive Noninvasive Means of Sequencing and Tracking M-Protein in the Blood of Multiple Myeloma Patients

The amino acid sequence of the M-protein for multiple myeloma is unique compared to the polyclonal antibodies in patients' blood. This uniqueness is exploited to develop an ultrasensitive M-protein detection method utilizing mass spectrometry (MS). The method involves the de novo amino acid sequencing of the full-length M-protein, and a targeted MS/MS assay to detect and quantify the unique M-protein sequence in serum samples. Healthy control serum spiked with NISTmAb and serial samples from an MM patient were used to demonstrate the ability of the platform to sequence and monitor a target M-protein. The de novo NISTmAb protein sequence obtained matched the published sequence, confirming the ability of the platform to accurately sequence a target M-protein in serum. NISTmAb was quantified down to 0.0002 g/dL in serum, a level hundreds of times more sensitive than conventional blood-based tests such as SPEP and IFE. The M-protein in the patient sample could be quantified throughout complete remission, demonstrating the utility of the assay to track M-protein considerably beyond the sensitivities of current blood-based tests. Notably, the assay detected a 2-fold rise in M-protein levels 10 months before any changes were detected by conventional IFE. The MS-based assay is highly sensitive, noninvasive, and requires only a small amount of serum, less than 100 μL. Sequencing data is deposited into PRIDE with identifier PXD022784, and quantification data can be found in Panorama Public with identifier PXD022980.

MASS SPECTROMETRY-BASED TECHNIQUES FOR DIRECT QUANTIFICATION OF HIGH IONIZATION ENERGY ELEMENTS IN SOLID MATERIALS-CHALLENGES AND PERSPECTIVES

The determination of nonmetals, first of all, the most electronegative ones-nitrogen, oxygen, fluorine, chlorine, and bromine, poses the highest challenge for element analysis. These elements are characterized by high reactivity, volatility, high ionization energy, and the absence of intensive spectral lines in the optical spectral range. Conventional techniques of their quantification include considerable "wet chemistry" stages so the application of these techniques for the solid sample is highly laborious and prone to uncontrollable uncertainties. Additionally, current development in material science and other areas requires the quantification of the elements at lower levels with good sensitivity. Owing to their robustness and flexibility, mass spectrometry techniques provide vast possibilities for the quantification, spatial and isotopic analysis, including the solutions for direct analysis of solids. The current review focuses on the application of major mass spectrometric techniques for the quantification of N, O, F, Cl, and Br in solid samples. The following techniques are mainly considered: thermal ionization mass spectrometry (TIMS), isotope-ratio MS (IRMS), secondary ion MS (SIMS), inductively coupled plasma MS (ICP-MS), and glow discharge MS (GDMS); as the most accessible and widely applied for the purpose. General ionization issues, advantages, limitations, and novel methodological solutions are discussed. © 2020 John Wiley & Sons Ltd.

Proteomic and Transcriptomic Analysis of Microviridae φX174 Infection Reveals Broad Upregulation of Host Escherichia coli Membrane Damage and Heat Shock Responses

A major part of the healthy human gut microbiome is the Microviridae bacteriophage, exemplified by the model φX174 phage, and their E. coli hosts. Although much has been learned from studying φX174 over the last half-century, until this work, the E. coli host response to infection has never been investigated in detail.

Measuring host-bacteriophage dynamics is an important approach to understanding bacterial survival functions and responses to infection. The model Microviridae bacteriophage φX174 is endemic to the human gut and has been studied for over 70 years, but the host response to infection has never been investigated in detail. To address this gap in our understanding of this important interaction within our microbiome, we have measured host Escherichia coli C proteomic and transcriptomic response to φX174 infection. We used mass spectrometry and RNA sequencing (RNA-seq) to identify and quantify all 11 φX174 proteins and over 1,700 E. coli proteins, enabling us to comprehensively map host pathways involved in φX174 infection. Most notably, we see significant host responses centered on membrane damage and remodeling, cellular chaperone and translocon activity, and lipoprotein processing, which we speculate is due to the peptidoglycan-disruptive effects of the φX174 lysis protein E on MraY activity. We also observe the massive upregulation of small heat shock proteins IbpA/B, along with other heat shock pathway chaperones, and speculate on how the specific characteristics of holdase protein activity may be beneficial for viral infections. Together, this study enables us to begin to understand the proteomic and transcriptomic host responses of E. coli to Microviridae infections and contributes insights to the activities of this important model host-phage interaction.

IMPORTANCE A major part of the healthy human gut microbiome is the Microviridae bacteriophage, exemplified by the model φX174 phage, and their E. coli hosts. Although much has been learned from studying φX174 over the last half-century, until this work, the E. coli host response to infection has never been investigated in detail. We reveal the proteomic and transcriptomic pathways differentially regulated during the φX174 infection cycle and uncover the details of a coordinated cellular response to membrane damage that results in increased lipoprotein processing and membrane trafficking, likely due to the phage antibiotic-like lysis protein. We also reveal that small heat shock proteins IbpA/B are massively upregulated during infection and that these holdase chaperones are highly conserved across the domains of life, indicating that reliance on them is likely widespread across viruses.

Proteomics applications in biomarker discovery and pathogenesis for abdominal aortic aneurysm

Introduction: Abdominal aortic aneurysm (AAA) is a common, complex, and life-threatening disease. Currently, the pathogenesis of AAA is not well understood. No biomarkers or specific drugs are available for AAA in clinical applications. Proteomics is a powerful tool in biomarker discovery, exploration of pathogenesis, and drug target identification.Areas covered: We review the application of mass spectrometry-based proteome analysis in AAA patients within the last ten years. Differentially expressed proteins associated with AAA were identified in multiple sample sources, including vascular tissue, intraluminal thrombus, tissue secretome, blood, and cells. Some potential disease biomarkers, pathogenic mechanisms, or therapeutic targets for AAA were discovered using proteome analysis. The challenges and prospects of proteomics applied to AAA are also discussed.Expert opinion: Since most of the previous proteomic studies used relatively small sample sizes, some promising biomarkers need to be validated in multicenter cohorts to accelerate their clinical application. With the rapid development of mass spectrometry technology, modification-specific proteomics and multi-omics research in the future will enhance our understanding of the pathogenesis of AAA and promote biomarker discovery and drug development for clinical translation.

Screening Platform Based on Inductively Coupled Plasma Mass Spectrometry for β-Site Amyloid Protein Cleaving Enzyme 1 (BACE1) Inhibitors

β-Site amyloid protein cleaving enzyme 1 (BACE1) is a promising therapeutic target for developing inhibitors to alleviate Alzheimer's disease (AD). Herein, we established an inductively coupled plasma mass spectrometry (ICPMS)-based inhibitor screening platform. A biotin-labeled lanthanide-coded peptide probe (LCPP; biotin-PEG₂-EVNLDAEC-DOTA-Ln) was designed to determine the activity of BACE1 and evaluate the degree of inhibition of inhibitors. The platform was first validated with two commercially available inhibitors (BSI I and BSI IV) in terms of IC₅₀ values and then applied to two newly designed inhibitors (inhibitors II and III) based on the crystal structure of BACE1 interacting with inhibitor I, and each of them contained an acylguanidine core structure. We found that their inhibition effects were improved as evaluated by the sensitive and accurate LCPP-ICPMS platform, demonstrating its ability for new drug screening.