Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

phuEGO: A Network-Based Method to Reconstruct Active Signaling Pathways From Phosphoproteomics Datasets

Signaling networks are critical for virtually all cell functions. Our current knowledge of cell signaling has been summarized in signaling pathway databases, which, while useful, are highly biased toward well-studied processes, and do not capture context specific network wiring or pathway cross-talk. Mass spectrometry-based phosphoproteomics data can provide a more unbiased view of active cell signaling processes in a given context, however, it suffers from low signal-to-noise ratio and poor reproducibility across experiments. While progress in methods to extract active signaling signatures from such data has been made, there are still limitations with respect to balancing bias and interpretability. Here we present phuEGO, which combines up-to-three-layer network propagation with ego network decomposition to provide small networks comprising active functional signaling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets. We applied phuEGO to five phosphoproteomics data sets from cell lines collected upon infection with SARS CoV2. PhuEGO was better able to identify common active functions across datasets and to point to a subnetwork enriched for known COVID-19 targets. Overall, phuEGO provides a flexible tool to the community for the improved functional interpretation of global phosphoproteomics datasets.

Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions

With the emergence of next-generation nucleotide sequencing and mass spectrometry-based proteomics and metabolomics tools, we have comprehensive and scalable methods to analyze the genes, transcripts, proteins, and metabolites of a multitude of biological systems. Despite the fascinating new molecular insights at the genome, transcriptome, proteome and metabolome scale, we are still far from fully understanding cellular organization, cell cycles and biology at the molecular level. Significant advances in sensitivity and depth for both sequencing as well as mass spectrometry-based methods allow the analysis at the single cell and single molecule level. At the same time, new tools are emerging that enable the investigation of molecular interactions throughout the central dogma of molecular biology. In this review, we provide an overview of established and recently developed mass spectrometry-based tools to probe metabolite-protein interactions-from individual interaction pairs to interactions at the proteome-metabolome scale.

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.

Identification of Mortalin as the Main Interactor of Mycalin A, a Poly-Brominated C-15 Acetogenin Sponge Metabolite, by MS-Based Proteomics

Mycalin A (MA) is a polybrominated C-15 acetogenin isolated from the marine sponge Mycale rotalis. Since this substance displays a strong antiproliferative bioactivity towards some tumour cells, we have now directed our studies towards the elucidation of the MA interactome through functional proteomic approaches, (DARTS and t-LIP-MS). DARTS experiments were performed on Hela cell lysates with the purpose of identifying MA main target protein(s); t-LiP-MS was then applied for an in-depth investigation of the MA-target protein interaction. Both these techniques exploit limited proteolysis coupled with MS analysis. To corroborate LiP data, molecular docking studies were performed on the complexes. Finally, biological and SPR analysis were conducted to explore the effect of the binding. Mortalin (GRP75) was identified as the MA's main interactor. This protein belongs to the Hsp70 family and has garnered significant attention due to its involvement in certain forms of cancer. Specifically, its overexpression in cancer cells appears to hinder the pro-apoptotic function of p53, one of its client proteins, because it becomes sequestered in the cytoplasm. Our research, therefore, has been focused on the possibility that MA might prevent this sequestration, promoting the re-localization of p53 to the nucleus and facilitating the apoptosis of tumor cells.

Megalin is involved in angiotensinogen-induced, angiotensin II-mediated ERK1/2 signaling to activate Na + -H + exchanger 3 in proximal tubules

BACKGROUND

Kidney angiotensin (Ang) II is produced mainly from liver-derived, glomerular-filtered angiotensinogen (AGT). Podocyte injury has been reported to increase the kidney Ang II content and induce Na + retention depending on the function of megalin, a proximal tubular endocytosis receptor. However, how megalin regulates the renal content and action of Ang II remains elusive.

METHODS

We used a mass spectrometry-based, parallel reaction-monitoring assay to quantitate Ang II in plasma, urine, and kidney homogenate of kidney-specific conditional megalin knockout (MegKO) and control (Ctl) mice. We also evaluated the pathophysiological changes in both mouse genotypes under the basal condition and under the condition of increased glomerular filtration of AGT induced by administration of recombinant mouse AGT (rec-mAGT).

RESULTS

Under the basal condition, plasma and kidney Ang II levels were comparable in the two mouse groups. Ang II was detected abundantly in fresh spot urine in conditional MegKO mice. Megalin was also found to mediate the uptake of intravenously administered fluorescent Ang II by PTECs. Administration of rec-mAGT increased kidney Ang II, exerted renal extracellular signal-regulated kinase 1/2 (ERK1/2) signaling, activated proximal tubular Na + -H + exchanger 3 (NHE3), and decreased urinary Na + excretion in Ctl mice, whereas these changes were suppressed but urinary Ang II was increased in conditional MegKO mice.

CONCLUSION

Increased glomerular filtration of AGT is likely to augment Ang II production in the proximal tubular lumen. Thus, megalin-dependent Ang II uptake should be involved in the ERK1/2 signaling that activates proximal tubular NHE3 in vivo , thereby causing Na + retention.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

Decoding Angiotensin Receptors: TOMAHAQ-Based Detection and Quantification of Angiotensin Type-1 and Type-2 Receptors

Background The renin-angiotensin system plays a crucial role in human physiology, and its main hormone, angiotensin, activates 2 G-protein-coupled receptors, the angiotensin type-1 and type-2 receptors, in almost every organ. However, controversy exists about the location, distribution, and expression levels of these receptors. Concerns have been raised over the low sensitivity, low specificity, and large variability between lots of commercially available antibodies for angiotensin type-1 and type-2 receptors, which makes it difficult to reconciliate results of different studies. Here, we describe the first non-antibody-based sensitive and specific targeted quantitative mass spectrometry assay for angiotensin receptors. Methods and Results Using a technique that allows targeted analysis of multiple peptides across multiple samples in a single mass spectrometry analysis, known as TOMAHAQ (triggered by offset, multiplexed, accurate mass, high resolution, and absolute quantification), we have identified and validated specific human tryptic peptides that permit identification and quantification of angiotensin type-1 and type-2 receptors in biological samples. Several peptide sequences are conserved in rodents, making these mass spectrometry assays amenable to both preclinical and clinical studies. We have used this method to quantify angiotensin type-1 and type-2 receptors in postmortem frontal cortex samples of older adults (n=28) with Alzheimer dementia. We correlated levels of angiotensin receptors to biomarkers classically linked to renin-angiotensin system activation, including oxidative stress, inflammation, amyloid-β load, and paired helical filament-tau tangle burden. Conclusions These robust high-throughput assays will not only catalyze novel mechanistic studies in the angiotensin research field but may also help to identify patients with an unbalanced angiotensin receptor distribution who would benefit from angiotensin receptor blocker treatment.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

Proteome dynamics during transition from exponential to stationary phase under aerobic and anaerobic conditions in yeast

The yeast Saccharomyces cerevisiae is a widely used eukaryotic model organism and a promising cell factory for industry. However, despite decades of research, the regulation of its metabolism is not yet fully understood, and its complexity represents a major challenge for engineering and optimising biosynthetic routes. Recent studies have demonstrated the potential of resource and proteomic allocation data in enhancing models for metabolic processes. However, comprehensive and accurate proteome dynamics data that can be used for such approaches are still very limited. Therefore, we performed a quantitative proteome dynamics study to comprehensively cover the transition from exponential to stationary phase for both aerobically and anaerobically grown yeast cells. The combination of highly controlled reactor experiments, biological replicates and standardised sample preparation procedures ensured reproducibility and accuracy. Additionally, we selected the CEN.PK lineage for our experiments because of its relevance for both fundamental and applied research. Together with the prototrophic, standard haploid strain CEN.PK113-7D, we also investigated an engineered strain with genetic minimisation of the glycolytic pathway, resulting in the quantitative assessment of 54 proteomes. The anaerobic cultures showed remarkably less proteome-level changes compared to the aerobic cultures, during transition from the exponential to the stationary phase as a consequence of the lack of the diauxic shift in the absence of oxygen. These results support the notion that anaerobically growing cells lack resources to adequately adapt to starvation. This proteome dynamics study constitutes an important step towards better understanding of the impact of glucose exhaustion and oxygen on the complex proteome allocation process in yeast. Finally, the established proteome dynamics data provide a valuable resource for the development of resource allocation models as well as for metabolic engineering efforts.

A critical path to producing high quality, reproducible data from quantitative western blot experiments

Western blotting experiments were initially performed to detect a target protein in a complex biological sample and more recently, to measure relative protein abundance. Chemiluminescence coupled with film-based detection was traditionally the gold standard for western blotting but accurate and reproducible quantification has been a major challenge from this methodology. The development of sensitive, camera-based detection technologies coupled with an updated technical approach permits the production of reproducible, quantitative data. Fluorescence reagent and detection solutions are the latest innovation in western blotting but there remains questions and debate concerning their relative sensitivity and dynamic range versus chemiluminescence. A methodology to optimize and produce excellent, quantitative western blot results with rigorous data analysis from membranes probed with both fluorescent and chemiluminescent antibodies is described. The data reveal when and how to apply these detection methods to achieve reproducible data with a stepwise approach to data processing for quantitative analysis.

Quantitative Cell Proteomic Atlas: Pathway-Scale Targeted Mass Spectrometry for High-Resolution Functional Profiling of Cell Signaling

In spite of extensive studies of cellular signaling, many fundamental processes such as pathway integration, cross-talk, and feedback remain poorly understood. To enable integrated and quantitative measurements of cellular biochemical activities, we have developed the Quantitative Cell Proteomics Atlas (QCPA). QCPA consists of panels of targeted mass spectrometry assays to determine the abundance and stoichiometry of regulatory post-translational modifications of sentinel proteins from most known physiologic and pathogenic signaling pathways in human cells. QCPA currently profiles 1 913 peptides from 469 effectors of cell surface signaling, apoptosis, stress response, gene expression, quiescence, and proliferation. For each protein, QCPA includes triplets of isotopically labeled peptides covering known post-translational regulatory sites to determine their stoichiometries and unmodified protein regions to measure total protein abundance. The QCPA framework incorporates analytes to control for technical variability of sample preparation and mass spectrometric analysis, including TrypQuant, a synthetic substrate for accurate quantification of proteolysis efficiency for proteins containing chemically modified residues. The ability to precisely and accurately quantify most known signaling pathways should enable improved chemoproteomic approaches for the comprehensive analysis of cell signaling and clinical proteomics of diagnostic specimens. QCPA is openly available at https://qcpa.mskcc.org.

Altered Bioavailability and Pharmacokinetics in Crohn's Disease: Capturing Systems Parameters for PBPK to Assist with Predicting the Fate of Orally Administered Drugs

Backgrond and Objective

Crohn’s disease (CD) is a chronic inflammatory bowel disease that affects a wide age range. Hence, CD patients receive a variety of drugs over their life beyond those used for CD itself. The changes to the integrity of the intestine and its drug metabolising enzymes and transporters (DMETs) can alter the oral bioavailability of drugs. However, there are other changes in systems parameters determining the fate of drugs in CD, and understanding these is essential for dose adjustment in patients with CD.

Methods

The current analysis gathered all the available clinical data on the kinetics of drugs in CD (by March 2021), focusing on orally administered small molecule drugs. A meta-analysis of the systems parameters affecting oral drug pharmacokinetics was conducted. The systems information gathered on intestine, liver and blood proteins and other physiological parameters was incorporated into a physiologically based pharmacokinetic (PBPK) platform to create a virtual population of CD patients, with a view for guiding dose adjustment in the absence of clinical data in CD.

Results

There were no uniform trends in the reported changes in reported oral bioavailability. The nature of the drug as well as the formulation affected the direction and magnitude of variation in kinetics in CD patients relative to healthy volunteers. Even for the same drug, the reported changes in exposure varied, possibly due to a lack of distinction between the activity states of CD. The highest alteration was seen with S-verapamil and midazolam, 8.7- and 5.3-fold greater exposure, respectively, in active CD patients relative to healthy volunteers. Only one report was available on liver DMETs in CD, and indicated reduced CYP3A4 activity. In a number of reports, mRNA expression of DMETs in the ileum and colon of CD patients was measured, focussing on P-glycoprotein (p-gp) transporter and CYP3A4 enzyme, and showed contradictory results. No data were available on protein expression in duodenum and jejunum despite their dominant role in oral drug absorption.

Conclusion

There are currently inadequate dedicated clinical or quantitative proteomic studies in CD to enable predictive PBPK models with high confidence and adequate verification. The PBPK models for CD with the available systems parameters were able to capture the major physiological influencers and the gaps to be filled by future research. Quantification of DMETs in the intestine and the liver in CD is warranted, alongside well-defined clinical drug disposition studies with a number of index drugs as biomarkers of changes in DMETs in these patients, to avoid large-scale dedicated studies for every drug to determine the effects of disease on the drug’s metabolism and disposition and the consequential safety and therapeutic concerns.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40262-022-01169-4.

Dystrophin Protein Quantification as a Duchenne Muscular Dystrophy Diagnostic Biomarker in Dried Blood Spots Using Multiple Reaction Monitoring Tandem Mass Spectrometry: A Preliminary Study

Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder characterized by progressive muscle loss, leading to difficulties in movement. Mutations in the DMD gene that code for the protein dystrophin are responsible for the development of DMD disorder, where the synthesis of this protein is completely halted. Therefore, circulating dystrophin protein could be a promising biomarker of DMD disease. Current methods for diagnosing DMD have sensitivity, specificity, and reproducibility limitations. Herein, a quantitative liquid chromatography-tandem spectrometry (LC-MS/MS) technique in multiple reaction monitoring (MRM) mode was designed and validated for accurate dystrophin protein measurement in a dried blood spot (DBS). The method was successfully validated on the basis of international guidelines regarding calibration curves, precision, and accuracy. In addition, patients and healthy controls were used to test the amount of dystrophin protein circulating in DBS samples as a potential biomarker for DMD disorders. DMD patients were found to have considerably lower levels than controls. To the best of our knowledge, this is the first study to report dystrophin levels in DBS through LC-MS/MS as a diagnostic marker for DMD to the proposed MRM method, providing a highly specific and sensitive approach to dystrophin quantification in a DBS that can be applied in DMD screening.

Localization of EccA3 at the growing pole in Mycobacterium smegmatis

Background

Bacteria require specialized secretion systems for the export of molecules into the extracellular space to modify their environment and scavenge for nutrients. The ESX-3 secretion system is required by mycobacteria for iron homeostasis. The ESX-3 operon encodes for one cytoplasmic component (EccA₃) and five membrane components (EccB3 – EccE3 and MycP₃). In this study we sought to identify the sub-cellular location of EccA₃ of the ESX-3 secretion system in mycobacteria.

Results

Fluorescently tagged EccA₃ localized to a single pole in the majority of Mycobacterium smegmatis cells and time-lapse fluorescent microscopy identified this pole as the growing pole. Deletion of ESX-3 did not prevent polar localization of fluorescently tagged EccA₃, suggesting that EccA₃ unipolar localization is independent of other ESX-3 components. Affinity purification - mass spectrometry was used to identify EccA₃ associated proteins which may contribute to the localization of EccA₃ at the growing pole. EccA₃ co-purified with fatty acid metabolism proteins (FAS, FadA3, KasA and KasB), mycolic acid synthesis proteins (UmaA, CmaA1), cell division proteins (FtsE and FtsZ), and cell shape and cell cycle proteins (MurS, CwsA and Wag31). Secretion system related proteins Ffh, SecA1, EccA1, and EspI were also identified.

Conclusions

Time-lapse microscopy demonstrated that EccA3 is located at the growing pole in M. smegmatis. The co-purification of EccA₃ with proteins known to be required for polar growth, mycolic acid synthesis, the Sec secretion system (SecA1), and the signal recognition particle pathway (Ffh) also suggests that EccA₃ is located at the site of active cell growth.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02554-6.

Application of Parallel Reaction Monitoring in 15N Labeled Samples for Quantification

Accurate relative quantification is critical in proteomic studies. The incorporation of stable isotope ¹⁵N to plant-expressed proteins in vivo is a powerful tool for accurate quantification with a major advantage of reducing preparative and analytical variabilities. However, ¹⁵N labeling quantification has several challenges. Less identifications are often observed in the heavy-labeled samples because of incomplete labeling, resulting in missing values in reciprocal labeling experiments. Inaccurate quantification can happen when there is contamination from co-eluting peptides or chemical noise in the MS¹ survey scan. These drawbacks in quantification can be more pronounced in less abundant but biologically interesting proteins, which often have very few identified peptides. Here, we demonstrate the application of parallel reaction monitoring (PRM) to ¹⁵N labeled samples on a high resolution, high mass accuracy Orbitrap mass spectrometer to achieve reliable quantification even of low abundance proteins in samples.

Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases

Rapid and precise diagnostic methods are required to control emerging infectious diseases effectively. Human body fluids are attractive clinical samples for discovering diagnostic targets because they reflect the clinical statuses of patients and most of them can be obtained with minimally invasive sampling processes. Body fluids are good reservoirs for infectious parasites, bacteria, and viruses. Therefore, recent clinical proteomics methods have focused on body fluids when aiming to discover human- or pathogen-originated diagnostic markers. Cutting-edge liquid chromatography-mass spectrometry (LC-MS)-based proteomics has been applied in this regard; it is considered one of the most sensitive and specific proteomics approaches. Here, the clinical characteristics of each body fluid, recent tandem mass spectroscopy (MS/MS) data-acquisition methods, and applications of body fluids for proteomics regarding infectious diseases (including the coronavirus disease of 2019 [COVID-19]), are summarized and discussed.

Quantitative Detection of Protein Splice Variants by Selected Reaction Monitoring (SRM) Mass Spectrometry

Molecular diversification of the cellular proteome through alternative splicing has emerged as an important biological principle. However, the lack of tools to specifically detect and quantify proteoforms (Smith et al., Nat Methods 10:186-187, 2013) is a major impediment to functional studies. Recently, biological mass spectrometry (MS) has undergone impressive advances (Mann, Nat Rev Mol Cell Biol 17:678, 2016), including the generation of a highly diverse set of biological applications (Aebersold and Mann, Nature 537:347-355, 2016), and has demonstrated to be an essential tool to address many biological questions (Savitski et al., Science 346:1255784, 2014; Rinner et al., Nat Methods 5:315-318, 2008). In particular, targeted LC-MS, with its high selectivity and specificity, is ideally suited for the precise and sensitive quantification of specific proteins and their proteoforms (Picotti and Aebersold, Nat Methods 9:555-566, 2012). We describe in detail the application of this workflow applied to dissect the molecular diversity of the synaptic adhesion proteins and their splicing-derived proteoforms (Schreiner et al., Elife 4:e07794, 2015).

Automated Multidimensional Nanoscale Chromatography for Ultrasensitive Targeted Mass Spectrometry

Recent advances in nanoscale separations and high-resolution mass spectrometry permit highly sensitive and accurate analyses of complex protein mixtures. Here, we describe improved methods for nanoscale multidimensional chromatography coupled to targeted mass spectrometry (tMS) to achieve ultrasensitive quantification of peptides in complex proteomes. The presented chromatographic system consists of capillary strong-cation exchange (SCX) chromatography column, from which peptides are eluted directly onto high-resolution reversed-phase (RP) analytical columns and nanoelectrospray ion source. SCX prefractionation is used to separate phosphorylated peptides, permitting their ultrasensitive quantification. Resolution and robustness of this chromatographic system, together with the orthogonality of SCX and RP separations, permit scheduling of large panels of targeted MS assays. This design also enables seamless scaling to three-dimensional separations, thereby enabling large-scale, ultrasensitive quantitative proteomics.

Single-Step Affinity Purification (ssAP) and Mass Spectrometry of Macromolecular Complexes in the Yeast S. cerevisiae

Cellular functions are mostly defined by the dynamic interactions of proteins within macromolecular networks. Deciphering the composition of macromolecular complexes and their dynamic rearrangements is the key to get a comprehensive picture of cellular behavior and to understand biological systems. In the past two decades, affinity purification coupled to mass spectrometry has become a powerful tool to comprehensively study interaction networks and their assemblies. To overcome initial limitations of the approach, in particular, the effect of protein and RNA degradation, loss of transient interactors, and poor overall yield of intact complexes from cell lysates, various modifications to affinity purification protocols have been devised over the years. In this chapter, we describe a rapid single-step affinity purification method for the efficient isolation of dynamic macromolecular complexes. The technique employs cell lysis by cryo-milling, which ensures nondegraded starting material in the submicron range, and magnetic beads, which allow for dense antibody-conjugation and thus rapid complex isolation, while avoiding loss of transient interactions. The method is epitope tag-independent, and overcomes many of the previous limitations to produce large interactomes with almost no contamination. The protocol as described here has been optimized for the yeast S. cerevisiae.

In-depth assembly of organ and development dissected Picrorhiza kurroa proteome map using mass spectrometry

BACKGROUND

Picrorhiza kurroa Royle ex Benth. being a rich source of phytochemicals, is a promising high altitude medicinal herb of Himalaya. The medicinal potential is attributed to picrosides i.e. iridoid glycosides, which synthesized in organ-specific manner through highly complex pathways. Here, we present a large-scale proteome reference map of P. kurroa, consisting of four morphologically differentiated organs and two developmental stages.

RESULTS

We were able to identify 5186 protein accessions (FDR < 1%) providing a deep coverage of protein abundance array, spanning around six orders of magnitude. Most of the identified proteins are associated with metabolic processes, response to abiotic stimuli and cellular processes. Organ specific sub-proteomes highlights organ specialized functions that would offer insights to explore tissue profile for specific protein classes. With reference to P. kurroa development, vegetative phase is enriched with growth related processes, however generative phase harvests more energy in secondary metabolic pathways. Furthermore, stress-responsive proteins, RNA binding proteins (RBPs) and post-translational modifications (PTMs), particularly phosphorylation and ADP-ribosylation play an important role in P. kurroa adaptation to alpine environment. The proteins involved in the synthesis of secondary metabolites are well represented in P. kurroa proteome. The phytochemical analysis revealed that marker compounds were highly accumulated in rhizome and overall, during the late stage of development.

CONCLUSIONS

This report represents first extensive proteomic description of organ and developmental dissected P. kurroa, providing a platform for future studies related to stress tolerance and medical applications.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

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Advanced acquisition methods improve focus of mass spectrometers on target peptides.

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This review discusses existing methods based on two strategies.

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Retention time adjustment-based methods enable intelligent scheduling of peptide RTs.

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In spike-in triggered acquisition methods targeted scans are initiated by spike-ins.

Building Personalized Cancer Therapeutics through Multi-Omics Assays and Bacteriophage-Eukaryotic Cell Interactions

Bacteriophage-eukaryotic cell interaction provides the biological foundation of Phage Display technology, which has been widely adopted in studies involving protein-protein and protein-peptide interactions, and it provides a direct link between the proteins and the DNA encoding them. Phage display has also facilitated the development of new therapeutic agents targeting personalized cancer mutations. Proteins encoded by mutant genes in cancers can be processed and presented on the tumor cell surface by human leukocyte antigen (HLA) molecules, and such mutant peptides are called Neoantigens. Neoantigens are naturally existing tumor markers presented on the cell surface. In clinical settings, the T-cell recognition of neoantigens is the foundation of cancer immunotherapeutics. This year, we utilized phage display to successfully develop the 1st antibody-based neoantigen targeting approach for next-generation personalized cancer therapeutics. In this article, we discussed the strategies for identifying neoantigens, followed by using phage display to create personalized cancer therapeutics-a complete pipeline for personalized cancer treatment.

Novel Strategies to Address the Challenges in Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is a powerful technology for comprehensively characterizing proteoforms to decipher post-translational modifications (PTMs) together with genetic variations and alternative splicing isoforms toward a proteome-wide understanding of protein functions. In the past decade, top-down proteomics has experienced rapid growth benefiting from groundbreaking technological advances, which have begun to reveal the potential of top-down proteomics for understanding basic biological functions, unraveling disease mechanisms, and discovering new biomarkers. However, many challenges remain to be comprehensively addressed. In this Account & Perspective, we discuss the major challenges currently facing the top-down proteomics field, particularly in protein solubility, proteome dynamic range, proteome complexity, data analysis, proteoform-function relationship, and analytical throughput for precision medicine. We specifically review the major technology developments addressing these challenges with an emphasis on our research group's efforts, including the development of top-down MS-compatible surfactants for protein solubilization, functionalized nanoparticles for the enrichment of low-abundance proteoforms, strategies for multidimensional chromatography separation of proteins, and a new comprehensive user-friendly software package for top-down proteomics. We have also made efforts to connect proteoforms with biological functions and provide our visions on what the future holds for top-down proteomics.

The C-Mannosylome of Human Induced Pluripotent Stem Cells Implies a Role for ADAMTS16 C-Mannosylation in Eye Development

C-mannosylation is a modification of tryptophan residues with a single mannose and can affect protein folding, secretion, and/or function. To date, only a few proteins have been demonstrated to be C-mannosylated, and studies that globally assess protein C-mannosylation are scarce. To interrogate the C-mannosylome of human induced pluripotent stem cells, we compared the secretomes of CRISPR–Cas9 mutants lacking either the C-mannosyltransferase DPY19L1 or DPY19L3 to WT human induced pluripotent stem cells using MS-based quantitative proteomics. The secretion of numerous proteins was reduced in these mutants, including that of A Disintegrin And Metalloproteinase with ThromboSpondin Motifs 16 (ADAMTS16), an extracellular protease that was previously reported to be essential for optic fissure fusion in zebrafish eye development. To test the functional relevance of this observation, we targeted dpy19l1 or dpy19l3 in embryos of the Japanese rice fish medaka (Oryzias latipes) by CRISPR–Cas9. We observed that targeting of dpy19l3 partially caused defects in optic fissure fusion, called coloboma. We further showed in a cellular model that DPY19L1 and DPY19L3 mediate C-mannosylation of a recombinantly expressed thrombospondin type 1 repeat of ADAMTS16 and thereby support its secretion. Taken together, our findings imply that DPY19L3-mediated C-mannosylation is involved in eye development by assisting secretion of the extracellular protease ADAMTS16.

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TSR1 of ADAMTS16 can be C-mannosylated.

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Deletion of DPY19L1 or DPY19L3 in hiPSCs caused reduced secretion of ADAMTS16.

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Targeting of dpy19l3 in medaka occasionally led to coloboma.

Systematic Comparison of Cell Wall-Related Proteins of Different Yeasts

Yeast cell walls have two major roles, to preserve physical integrity of the cell, and to ensure communication with surrounding molecules and cells. While the first function requires evolutionary conserved polysaccharide network synthesis, the second needs to be flexible and provide adaptability to different habitats and lifestyles. In this study, the comparative in silico analysis of proteins required for cell wall biosynthesis and functions containing 187 proteins of 92 different yeasts was performed in order to assess which proteins were broadly conserved among yeasts and which were more species specific. Proteins were divided into several groups according to their role and localization. As expected, many Saccharomyces cerevisiae proteins involved in protein glycosylation, glycosylphosphatidylinositol (GPI) synthesis and the synthesis of wall polysaccharides had orthologues in most other yeasts. Similarly, a group of GPI anchored proteins involved in cell wall biosynthesis (Gas proteins and Dfg5p/Dcw1p) and other non-GPI anchored cell wall proteins involved in the wall synthesis and remodeling were highly conserved. However, GPI anchored proteins involved in flocculation, aggregation, cell separation, and those of still unknown functions were not highly conserved. The proteins localized in the cell walls of various yeast species were also analyzed by protein biotinylation and blotting. Pronounced differences were found both in the patterns, as well as in the overall amounts of different groups of proteins. The amount of GPI-anchored proteins correlated with the mannan to glucan ratio of the wall. Changes of the wall proteome upon temperature shift to 42 °C were detected.

Development and Multiple Validation of the Protein Multi-marker Panel for Diagnosis of Pancreatic Cancer

PURPOSE

To develop and validate a protein-based, multi-marker panel that provides superior pancreatic ductal adenocarcinoma (PDAC) detection abilities with sufficient diagnostic performance.

EXPERIMENTAL DESIGN

A total of 959 plasma samples from patients at multiple medical centers were used. To construct an optimal, diagnostic, multi-marker panel, we applied data preprocessing procedure to biomarker candidates. The multi-marker panel was developed using a training set comprised of 261 PDAC cases and 290 controls. Subsequent evaluations were performed in a validation set comprised of 65 PDAC cases and 72 controls. Further validation was performed in an independent set comprised of 75 PDAC cases and 47 controls.

RESULTS

A multi-marker panel containing 14 proteins was developed. The multi-marker panel achieved AUCs of 0.977 and 0.953 for the training set and validation set, respectively. In an independent validation set, the multi-marker panel yielded an AUC of 0.928. The diagnostic performance of the multi-marker panel showed significant improvements compared with carbohydrate antigen (CA) 19-9 alone (training set AUC = 0.977 vs. 0.872, P < 0.001; validation set AUC = 0.953 vs. 0.832, P < 0.01; independent validation set AUC = 0.928 vs. 0.771, P < 0.001). When the multi-marker panel and CA 19-9 were combined, the diagnostic performance of the combined panel was improved for all sets.

CONCLUSIONS

This multi-marker panel and the combined panel showed statistically significant improvements in diagnostic performance compared with CA 19-9 alone and has the potential to complement CA 19-9 as a diagnostic marker in clinical practice.

Mass-Spectrometry-Based Near-Complete Draft of the Saccharomyces cerevisiae Proteome

Proteomics approaches designed to catalogue all open reading frames (ORFs) under a defined set of growth conditions of an organism have flourished in recent years. However, no proteome has been sequenced completely so far. Here, we generate the largest yeast proteome data set, including 5610 identified proteins, using a strategy based on optimized sample preparation and high-resolution mass spectrometry. Among the 5610 identified proteins, 94.1% are core proteins, which achieves near-complete coverage of the yeast ORFs. Comprehensive analysis of missing proteins showed that proteins are missed mainly due to physical properties. A review of protein abundance shows that our proteome encompasses a uniquely broad dynamic range. Additionally, these values highly correlate with mRNA abundance, implying a high level of accuracy, sensitivity, and precision. We present examples of how the data could be used, including reannotating gene localization, providing expression evidence of pseudogenes. Our near-complete yeast proteome data set will be a useful and important resource for further systematic studies.

DIA-based systems biology approach unveils E3 ubiquitin ligase-dependent responses to a metabolic shift

The yeast Saccharomyces cerevisiae is a powerful model system for systems-wide biology screens and large-scale proteomics methods. Nearly complete proteomics coverage has been achieved owing to advances in mass spectrometry. However, it remains challenging to scale this technology for rapid and high-throughput analysis of the yeast proteome to investigate biological pathways on a global scale. Here we describe a systems biology workflow employing plate-based sample preparation and rapid, single-run, data-independent mass spectrometry analysis (DIA). Our approach is straightforward, easy to implement, and enables quantitative profiling and comparisons of hundreds of nearly complete yeast proteomes in only a few days. We evaluate its capability by characterizing changes in the yeast proteome in response to environmental perturbations, identifying distinct responses to each of them and providing a comprehensive resource of these responses. Apart from rapidly recapitulating previously observed responses, we characterized carbon source-dependent regulation of the GID E3 ligase, an important regulator of cellular metabolism during the switch between gluconeogenic and glycolytic growth conditions. This unveiled regulatory targets of the GID ligase during a metabolic switch. Our comprehensive yeast system readout pinpointed effects of a single deletion or point mutation in the GID complex on the global proteome, allowing the identification and validation of targets of the GID E3 ligase. Moreover, this approach allowed the identification of targets from multiple cellular pathways that display distinct patterns of regulation. Although developed in yeast, rapid whole-proteome-based readouts can serve as comprehensive systems-level assays in all cellular systems.

Selected reaction monitoring for the quantification of Escherichia coli ribosomal proteins

Ribosomes are the sophisticated machinery that is responsible for protein synthesis in a cell. Recently, quantitative mass spectrometry (qMS) have been successfully applied for understanding the dynamics of protein complexes. Here, we developed a highly specific and reproducible method to quantify all ribosomal proteins (r-proteins) by combining selected reaction monitoring (SRM) and isotope labeling. We optimized the SRM methods using purified ribosomes and Escherichia coli lysates and verified this approach as detecting 41 of the 54 r-proteins separately synthesized in E. coli S30 extracts. The SRM methods will enable us to utilize qMS as a highly specific analytical tool in the research of E. coli ribosomes, and this methodology have potential to accelerate the understanding of ribosome biogenesis, function, and the development of engineered ribosomes with additional functions.

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

Utility of Proteomics in Emerging and Re-Emerging Infectious Diseases Caused by RNA Viruses

Emerging and re-emerging infectious diseases due to RNA viruses cause major negative consequences for the quality of life, public health, and overall economic development. Most of the RNA viruses causing illnesses in humans are of zoonotic origin. Zoonotic viruses can directly be transferred from animals to humans through adaptation, followed by human-to-human transmission, such as in human immunodeficiency virus (HIV), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and, more recently, SARS coronavirus 2 (SARS-CoV-2), or they can be transferred through insects or vectors, as in the case of Crimean-Congo hemorrhagic fever virus (CCHFV), Zika virus (ZIKV), and dengue virus (DENV). At the present, there are no vaccines or antiviral compounds against most of these viruses. Because proteins possess a vast array of functions in all known biological systems, proteomics-based strategies can provide important insights into the investigation of disease pathogenesis and the identification of promising antiviral drug targets during an epidemic or pandemic. Mass spectrometry technology has provided the capacity required for the precise identification and the sensitive and high-throughput analysis of proteins on a large scale and has contributed greatly to unravelling key protein-protein interactions, discovering signaling networks, and understanding disease mechanisms. In this Review, we present an account of quantitative proteomics and its application in some prominent recent examples of emerging and re-emerging RNA virus diseases like HIV-1, CCHFV, ZIKV, and DENV, with more detail with respect to coronaviruses (MERS-CoV and SARS-CoV) as well as the recent SARS-CoV-2 pandemic.

Assessment of Protein Content and Phosphorylation Level in Synechocystis sp. PCC 6803 under Various Growth Conditions Using Quantitative Phosphoproteomic Analysis

The photosynthetic apparatus and metabolic enzymes of cyanobacteria are subject to various controls, such as transcriptional regulation and post-translational modifications, to ensure that the entire cellular system functions optimally. In particular, phosphorylation plays key roles in many cellular controls such as enzyme activity, signal transduction, and photosynthetic apparatus restructuring. Therefore, elucidating the governing functions of phosphorylation is crucial to understanding the regulatory mechanisms underlying metabolism and photosynthesis. In this study, we determined protein content and phosphorylation levels to reveal the regulation of intracellular metabolism and photosynthesis in Synechocystis sp. PCC 6803; for this, we obtained quantitative data of proteins and their phosphorylated forms involved in photosynthesis and metabolism under various growth conditions (photoautotrophic, mixotrophic, heterotrophic, dark, and nitrogen-deprived conditions) using targeted proteomic and phosphoproteomic analyses with nano-liquid chromatography-triple quadrupole mass spectrometry. The results indicated that in addition to the regulation of protein expression, the regulation of phosphorylation levels of cyanobacterial photosynthetic apparatus and metabolic enzymes was pivotal for adapting to changing environmental conditions. Furthermore, reduced protein levels of CpcC and altered phosphorylation levels of CpcB, ApcA, OCP, and PsbV contributed to the cellular response of the photosynthesis apparatus to nitrogen deficiency.

Parallel Notched Gas-Phase Enrichment for Improved Proteome Identification and Quantification with Fast Spectral Acquisition Rates

Gas-phase fractionation enables better quantitative accuracy, improves signal-to-noise ratios, and increases sensitivity in proteomic analyses. However, traditional gas-phase enrichment, which relies upon a large continuous bin, results in suboptimal enrichment, as most chromatographic separations are not 100% orthogonal relative to the first MS dimension (MS1m/z). As such, ions with similar m/z values tend to elute at the same retention time, which prevents the partitioning of narrow precursor m/z distributions into a few large continuous gas-phase enrichment bins. To overcome this issue, we developed and tested the use of notched isolation waveforms, which simultaneously isolate multiple discrete m/z windows in parallel (e.g., 650-700 m/z and 800-850 m/z). By comparison to a canonical gas-phase fractionation method, notched waveforms do not require bin optimization via in silico digestion or wasteful sample injections to isolate multiple precursor windows. Importantly, the collection of all m/z bins simultaneously using the isolation waveform does not suffer from the sensitivity and duty cycle pitfalls inherent to sequential collection of multiple m/z bins. Applying a notched injection waveform provided consistent enrichment of precursor ions, which resulted in improved proteome depth with greater coverage of low-abundance proteins. Finally, using a reductive dimethyl labeling approach, we show that notched isolation waveforms increase the number of quantified peptides with improved accuracy and precision across a wider dynamic range.

Automated, Generic Reagent and Ultratargeted 2D-LC-MS/MS Enabling Quantification of Biotherapeutics and Soluble Targets down to pg/mL Range in Serum

Mass spectrometry has recently emerged as a powerful analytical tool for the assessment of pharmacokinetics and biomarkers in drug development. Compared with ligand binding assays, a major advantage of mass spectrometry-based assays is that they are less dependent on high quality binding reagents, while a key limitation is the relatively lower sensitivity. To address the sensitivity issue, we have developed a generic reagent, ultratargeted two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) method which combines commercially available protein A affinity capture, targeted analyte isolation by 2D-LC, and targeted detection by multiple reaction monitoring (MRM). A targeted-2D-with-dilution configuration was designed to automate 2D-LC-MS/MS. This method was systematically evaluated using an anti-CD22 monoclonal antibody spiked into monkey and human serum, where lower limits of quantification (LLOQ) of 0.78 and 1.56 ng/mL were achieved, respectively. This represents an over 100-fold improvement in assay sensitivity compared to the conventional LC-MS/MS method. The performance of the method was further confirmed by analyzing another monoclonal antibody, bevacizumab, as well as a soluble antigen, circulating PD-L1. The results indicate that our method enables quantification of antibody therapeutics and antigen biomarkers in both clinical and nonclinical samples in the pg/mL to low ng/mL range. Protein A affinity capture was employed as a universal sample preparation procedure applicable to both full-length antibody therapeutics and antibody-antigen complexes. This novel method is also fully automated and proven to be highly robust for routine bioanalysis in drug development.

Mass Spectrometry of Human Transporters

Transporters are key to understanding how an individual will respond to a particular dose of a drug. Two patients with similar systemic concentrations may have quite different local concentrations of a drug at the required site. The transporter profile of any individual depends upon a variety of genetic and environmental factors, including genotype, age, and diet status. Robust models (virtual patients) are therefore required and these models are data hungry. Necessary data include quantitative transporter profiles at the relevant organ. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) is currently the most powerful method available for obtaining this information. Challenges include sourcing the tissue, isolating the hydrophobic membrane-embedded transporter proteins, preparing the samples for MS (including proteolytic digestion), choosing appropriate quantification methodology, and optimizing the LC-MS/MS conditions. Great progress has been made with all of these, especially within the last few years, and is discussed here.

Evaluation of Aptamers as Affinity Reagents for an Enhancement of SRM-Based Detection of Low-Abundance Proteins in Blood Plasma

Selected reaction monitoring (SRM) is a mass spectrometric technique characterized by the exceptionally high selectivity and sensitivity of protein detection. However, even with this technique, the quantitative detection of low- and ultralow-abundance proteins in blood plasma, which is of great importance for the search and verification of novel protein disease markers, is a challenging task due to the immense dynamic range of protein abundance levels. One approach used to overcome this problem is the immunoaffinity enrichment of target proteins for SRM analysis, employing monoclonal antibodies. Aptamers appear as a promising alternative to antibodies for affinity enrichment. Here, using recombinant protein SMAD4 as a model target added at known concentrations to human blood plasma and SRM as a detection method, we investigated a relationship between the initial amount of the target protein and its amount in the fraction enriched with SMAD4 by an anti-SMAD4 DNA-aptamer immobilized on magnetic beads. It was found that the aptamer-based enrichment provided a 30-fold increase in the sensitivity of SRM detection of SMAD4. These results indicate that the aptamer-based affinity enrichment of target proteins can be successfully employed to improve quantitative detection of low-abundance proteins by SRM in undepleted human blood plasma.

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.

Developing a Robust Assay to Monitor and Quantify Key Players of Metabolic Pathways during Adipogenesis by Targeted Proteomics

Targeted data acquisition using nano liquid chromatrography (nano-LC) coupled mass spectrometry is an emerging approach when there is a need to quantify proteins with high accuracy, sensitivity, and reproducibility. Nevertheless, creating assays meeting all those criteria still remains a laborious task, especially when investigating low abundant proteins and small concentration changes. In this work a targeted data acquisition workflow is developed reducing time and effort to target and investigate key players of metabolic pathways during the process of adipocyte differentiation. This leads to accurate and sensitive quantification of proteins involved in the synthesis of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, the production of energy and reduction equivalents. Additionally low abundant signaling molecules part of the peroxisome proliferator-activated receptor gamma (PPARγ) and insulin signaling pathway with ≈400 for the insulin receptor substrate and 1100 copies per cell for PPARγ are determined.

Technologies to improve the sensitivity of existing chromatographic methods used for bioanalytical studies

Chromatographic method has long been recognized as the most widely used separation method in bioanalytical research. However, the relatively low sensitivity of existing chromatographic methods remains a significant challenge, as the requirements for experimental procedures become more demanding. This review discusses the main causes for the low sensitivity of chromatographic methods and aims to introduce different technologies for enhancing their sensitivity in the following aspects: (i) different pretreatment methods for improving clean-up efficiency and recovery; (ii) derivatization step for altering the chromatographic behavior of analytes and enhancing MS ionization efficiency; (iii) optimal LC-MS conditions and appropriate separation mechanism; and (iv) applications of other chromatographic methods, including miniaturized LC, 2D-LC, 2D-GC, and supercritical fluid chromatography. Altogether, this review is devoted to summarizing the recent technologies reported in the literature and providing new strategies for the detection of bioanalytes.

Targeted Proteomics as a Tool for Quantifying Urine-Based Biomarkers

Mass spectrometry based proteomics approaches are routinely used to discover candidate biomarkers. These studies often use small number of samples to discover candidate proteins that are later validated on a large cohort of samples. Targeted proteomics has emerged as a powerful method for quantification of multiple proteins in complex biological matrix. Parallel reaction monitoring (PRM) and selected reaction monitoring (SRM) are two main methods of choice for quantifying and validating proteins across hundreds to thousands of samples. Over the years, many software tools have become available that enable the users to carry out the analysis. In this chapter, we describe selection of proteotypic peptides, sample preparation, generating a response curve, data acquisition and analysis of PRM data using Skyline software for targeted proteomics to quantify candidate markers in urine.

Incorporation of a unified protein abundance dataset into the Saccharomyces genome database

The identification and accurate quantitation of protein abundance has been a major objective of proteomics research. Abundance studies have the potential to provide users with data that can be used to gain a deeper understanding of protein function and regulation and can also help identify cellular pathways and modules that operate under various environmental stress conditions. One of the central missions of the Saccharomyces Genome Database (SGD; https://www.yeastgenome.org) is to work with researchers to identify and incorporate datasets of interest to the wider scientific community, thereby enabling hypothesis-driven research. A large number of studies have detailed efforts to generate proteome-wide abundance data, but deeper analyses of these data have been hampered by the inability to compare results between studies. Recently, a unified protein abundance dataset was generated through the evaluation of more than 20 abundance datasets, which were normalized and converted to common measurement units, in this case molecules per cell. We have incorporated these normalized protein abundance data and associated metadata into the SGD database, as well as the SGD YeastMine data warehouse, resulting in the addition of 56 487 values for untreated cells grown in either rich or defined media and 28 335 values for cells treated with environmental stressors. Abundance data for protein-coding genes are displayed in a sortable, filterable table on Protein pages, available through Locus Summary pages. A median abundance value was incorporated, and a median absolute deviation was calculated for each protein-coding gene and incorporated into SGD. These values are displayed in the Protein section of the Locus Summary page. The inclusion of these data has enhanced the quality and quantity of protein experimental information presented at SGD and provides opportunities for researchers to access and utilize the data to further their research.

Combining Targeted and Untargeted Data Acquisition to Enhance Quantitative Plant Proteomics Experiments

Most quantitative proteomics experiments either target a limited number of selected proteins for quantification or quantify proteins on a broad scale in an untargeted manner. However, we recently demonstrated that experiments that have both targeted and untargeted components can be particularly advantageous. Using a combined targeted and untargeted liquid chromatography-tandem mass spectrometry data acquisition strategy termed TDA/DDA (shorthand for targeted data acquisition/data-dependent acquisition), which we applied to a model quantitative plant proteomics experiment performed on Arabidopsis, we demonstrated improved quantification of both targeted and untargeted proteins relative to purely untargeted experiments performed using conventional data-dependent acquisition (Hart-Smith et al. Front Plant Sci 8:1669, 2017). This suggests that many quantitative proteomics datasets earmarked for collection using data-dependent acquisition are likely to benefit from the use of TDA/DDA instead.This chapter describes how TDA/DDA liquid chromatography-tandem mass spectrometry methods can be created on commonly used mass spectrometric instrument platforms. It described how, using freely available software, tandem mass spectrometry inclusion lists designed to target proteins of hypothesized interest can be generated. Best practice implementation of these inclusion lists in TDA/DDA strategies is then described. Relative to conventional data-dependent acquisition, the liquid chromatography-tandem mass spectrometry methods created using these guidelines increase the chances of quantifying targeted proteins and can produce widespread improvements in the reproducibility of untargeted protein quantification, without compromising the total numbers of proteins quantified. They are compatible with different quantitative proteomics methodologies, including metabolic labeling, chemical labeling and label-free approaches, and can be used to create tailored assay libraries to aid the interpretation of quantitative proteomics data collected using data-independent acquisition.

Mass spectrometric approaches for profiling protein folding and stability

Protein stability reports on protein homeostasis, function, and binding interactions, such as to other proteins, metabolites and drugs. As such, there is a pressing need for technologies that can report on protein stability. The ideal technique could be applied in vitro or in vivo systems, proteome-wide, independently of matrix, under native conditions, with residue-level resolution, and on protein at endogenous levels. Mass spectrometry has rapidly become a preferred technology for identifying and quantifying proteins. As such, it has been increasingly incorporated into methodologies for interrogating protein stability and folding. Although no single technology can satisfy all desired applications, several emerging approaches have shown outstanding success at providing biological insight into the stability of the proteome. This chapter outlines some of these recent emerging technologies.

Unraveling and resolving inefficient glucolipid biosurfactants production through quantitative multiomics analyses of Starmerella bombicola strains

Glucolipids (GLs) are glycolipid biosurfactants with promising properties. These GLs are composed of glucose attached to a hydroxy fatty acid through a ω and/or ω-1 glycosidic linkage. Up until today these interesting molecules could only be produced using an engineered Starmerella bombicola strain (∆ugtB1::URA3 G9) producing GLs instead of sophorolipids, albeit with a very low average productivity (0.01 g·L^-1 ·h^-1 ). In this study, we investigated the reason(s) for this via reverse-transcription quantitative polymerase chain reaction and Liquid chromatography-multireaction monitoring-mass spectrometry. We found that all glycolipid biosynthetic genes and enzymes were downregulated in the ∆ugtB1 G9 strain in comparison to the wild type. The underlying reason for this downregulation was further investigated by performing quantitative metabolome comparison of the ∆ugtB1 G9 strain with the wild type and two other engineered strains also tinkered in their glycolipid biosynthetic gene cluster. This analysis revealed a clear distortion of the entire metabolism of the ∆ugtB1 G9 strain compared to all the other strains. Because the parental strain of the former was a spontaneous ∆ura3 mutant potentially containing other "hidden" mutations, a new GL production strain was generated based on a rationally engineered ∆ura3 mutant (PT36). Indeed, a 50-fold GL productivity increase (0.51 g·L^-1 ·h^-1 ) was obtained with the new ∆ugtB1::URA3 PT36 strain compared with the G9-based strain (0.01 g·L^-1 ·h^-1 ) in a 10 L bioreactor experiment, yielding 118 g/L GLs instead of 8.39 g/L. Purification was investigated and basic properties of the purified GLs were determined. This study forms the base for further development and optimization of S. bombicola as a production platform strain for (new) biochemicals.

Recent Advances in Microalgae Peptides: Cardiovascular Health Benefits and Analysis

There is now great interest in food protein hydrolysates and food-derived peptides, because they may provide numerous health benefits. Among other foodstuffs, microalgae appear to be sustainable sources of proteins and bioactive peptides that can be exploited in foods and functional formulations. This review considers protein hydrolysates and individual peptides that may be relevant in cardiovascular disease prevention because they mimic the functions of mediators involved in pathologic processes that represent relevant risk factors for cardiovascular disease development, such as hypercholesterolemia, hypertension, diabetes, inflammation, and oxidative status. Some of these peptides are also multifunctional (i.e., they offer more than one benefit). Moreover, the most efficient techniques for protein extraction and hydrolyzation are commented on, as well as the best methodologies for high-throughput detection and quantification. Finally, current challenges and critical issues are discussed.