De Novo Sequencing of Peptides from Tandem Mass Spectra and Applications in Proteogenomics.

The changes in protein expression are hallmarks of development and disease. Protein expression can be established qualitatively and quantitatively using mass spectrometry (MS). Samples are prepared, proteins extracted and then analyzed using MS and MS/MS. The resulting spectra need to be processed computationally to assign peptide spectrum match. Database searches employ sequence databases or spectral libraries for matching possible peptides with the measured spectra. This route is well established but fails when peptides are not found in sequence repositories. In this case, de novo sequencing of MS/MS spectra can be employed. Many computational algorithms that establish the peptide sequence from MS/MS spectrum alone are available. While de novo sequencing assigns a sequence to an MS/MS spectrum, this assignment can be used in further processes for genome annotation. For example, novel exons can be assigned, known exons can be extended, and splice sites can be validated at the protein level. We compiled an extensive list of such algorithms, grouped them, and discussed the selected approaches. We also provide a roadmap of how de novo sequencing can enter mainstream proteogenomic analysis. In the future, de novo predictions can be added to sample-specific protein databases, including RNA-seq translations. These enriched databases can then be used for proteogenomics studies with existing pipelines.

A Review of Protein Inference.

Protein inference is an often neglected though crucial step in most proteomic experiments. In the bottom-up proteomic approach, the actual molecules of interest, the proteins, are digested into peptides before measurement on a mass spectrometer. This approach introduces a loss of information: The actual proteins must be inferred based on the identified peptides. While this might seem trivial, there are certain problems, one of the biggest being the presence of peptides that are shared among proteins. These amino acid sequences can, based on the database used for identification, belong to more than one protein. If such peptides are identified in a sample, it cannot be said which proteins actually were in the sample, but only an estimate on the most probable proteins or protein groups can be given based on a predefined inference strategy.Here we describe the effect of the chosen database for peptide identification on the number of shared peptides. Afterward, the mainly used protein inference methods will be sketched, and the necessity of stringent false discovery rate on peptide and protein level is discussed. Finally, we explain how the tool "PIA or protein inference algorithms" can be used together with the workflow environment KNIME and OpenMS to perform protein inference in a common proteomic experiment.

Conformational Characterization of Peptides and Proteins by 193 nm Ultraviolet Photodissociation in the Collision Cell of a Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometer.

Ultraviolet photodissociation (UVPD) has been shown to be a versatile ion activation strategy for the characterization of peptides and intact proteins among other classes of biological molecules. Combining the high-performance mass spectrometry (MS/MS) capabilities of UVPD with the high-resolution separation of trapped ion mobility spectrometry (TIMS) presents an opportunity for enhanced structural elucidation of biological molecules. In the present work, we integrate a 193 nm excimer laser in a TIMS-time-of-flight (TIMS-TOF) mass spectrometer for UVPD in the collision cell and use it for the analysis of several mass-mobility-selected species of ubiquitin and myoglobin. The resultant data displayed differences in fragmentation that could be correlated with changes in protein conformation. Additionally, this mobility-resolved UVPD strategy was applied to collision-induced unfolded ions of ubiquitin to follow changes in fragmentation patterns relating to the extent of protein unfolding. This platform and methodology offer new opportunities for exploring how conformational variations are manifested in the fragmentation patterns of gas-phase ions.

Parallel sample processing for mass spectrometry-based single cell proteomics.

BACKGROUND: Single cell mass spectrometry (scMS) has shown great promise for label free proteomics analysis recently. To present single cell samples for proteomics analysis by MS is not a trivial task. Existing methods rely on robotic liquid handlers to scale up sample preparation throughput. The cost associated with specialized equipment hinders the broad adoption of these workflows, and the sequential sample processing nature limits the ultimate throughput. RESULTS: In this work, we report a parallel sample processing workflow that can simultaneously process 10 single cells without the need of robotic liquid handlers for scMS. This method utilized 3D printed microfluidic devices to form reagent arrays on a glass slide, and a magnetic beads-based streamlined sample processing workflow to present peptides for LC-MS detection. We optimized key operational parameters of the method and demonstrated the quantification consistency among 10 parallel processed samples. Finally, the utility of the method in differentiating cell lines and studying the proteome change induced by drug treatment were demonstrated. SIGNIFICANCE: The present method allows parallel sample processing for single cells without the need of expensive liquid handlers, which has great potential to further improve throughput and decrease the barrier for single cell proteomics.

Recent Trends in Therapeutic Drug Monitoring of Peptide Antibiotics.

Antimicrobial peptides take a specific position in the field of antibiotics (ATBs), however, from a large number of available molecules only a few of them were approved and are used in clinics. These therapeutic modalities play a crucial role in the management of diseases caused by multidrug-resistant bacterial pathogens and represent the last-line therapy for bacterial infections. Therefore, there is a demand for a rationale use of such ATBs based on optimization of the dosing strategy to minimize the risk of resistance and ensure the sustainable efficacy of the drug in real clinical practice. Therapeutic drug monitoring, as a measurement of drug concentration in the body fluids or tissues, results in the optimization of the patient´s medication and therapy outcome. This strategy is beneficial and could result in tailored therapy for different types of infection and the prolongation of the use and efficacy of ATBs in hospitals. This review paper provides an actual overview of approved antimicrobial peptides used in clinical practice and covers current trends in their analysis by convenient and advanced methodologies used for their identification and/or quantitation in biological matrices for therapeutic drug monitoring purposes. Special emphasis is given to the methods with perspective clinical outcomes.

Antioxidant activities of Saudi honey samples related to their content of short peptides.

This study explored the effect of geographical and floral origins on the antioxidant activities of Saudi honey samples related to their content of short peptides originated from honeybee proteins. The studied antioxidants were the total protein concentration, catalase activity, phenolic acids and flavonoids. The antioxidant activity assays included were the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay, the ferric reducing antioxidant power (FRAP) assay and Ascorbic acid Equivalent Antioxidant Capacity (AEAC). The studied honey samples were obtained from the southwestern region of Saudi Arabia, namely Asir (65) and Jazan (25). The floral origins of the honey samples were Acacia (51), Ziziphus (4) and polyfloral (35). The LC/MS technique was used to detect the short peptides and the mascot database was used to identify the short peptides, their precursor proteins and the protease enzymes that produce them. Jazan honey was characterized by high number of short peptides. The short peptides were originated from honeybee proteins by the action of proteases from the honeybees and bacteria. The antioxidant activity of the honey samples increase with the increase of their content of short peptides and proteins. The amino acids type and sequence of the short peptides qualify them to act as antioxidant, antimicrobial, anti-diabetic, anti-hypertension, immunomodulatory and cholesterol lowering peptides.

Methods to protein and peptide extraction from microalgae: a systematic review.

Currently, there is a demand for protein sources that do not use soil management or animal breeding. Among these sources we highlight the microorganisms, such cyanobacteria and microalgae, which have a simple growth using light, CO2, water and some mineral salts to generate high protein production. The extraction of these proteins depends on the method used. The most used methods for extracting bio-functional proteins are mechanical, chemical and enzymatic. The aim of this work is to analyze the protein extraction methods in microalgae using Scielo, ScienceDirect and NCBI (PubMed) electronic databases that made it possible to select original studies published in the last five years (2018-2023). A total of 2707 articles, 25 of which were selected for further analysis and subjected to risk of bias assessment. The genera Chlorella, Scenedesmus and Nannochloropsis were the most studied due to their high protein content. Mechanical methods and chemical hydrolysis are the most used methods, achieving an extraction yield of 46.0 % and 64.0 %, respectively. The best extraction results are obtained with a combination of methods, reaching up to 80.0 % yield. However, some aspects need to be observed to choose an ideal protein extraction method.

Greening Separation and Purification of Proteins and Peptides.

The increasing awareness of environmental issues and the transition to green analytical chemistry (GAC) have gained popularity among academia and industry in recent years. One of the principles of GAC is the reduction and replacement of toxic solvents with more sustainable and environmentally friendly ones. This review gives an overview of the advances in applying green solvents as an alternative to the traditional organic solvents for peptide and protein purification and analysis by liquid chromatography (LC) and capillary electrophoresis (CE) methods. The feasibility of using greener LC and CE methods is demonstrated through several application examples; however, there is still plenty of room for new developments to fully realize their potential and to address existing challenges. Thanks to the tunable properties of designer solvents, such as ionic liquids and deep eutectic solvents, and almost infinite possible mixtures of components for their production, it is possible that some new designer solvents could potentially surpass the traditional harmful solvents in the future. Therefore, future research should focus mainly on developing new solvent combinations and enhancing analytical instruments to be able to effectively work with green solvents.

Analysis of mitochondrial targeting signal cleavage and protein processing by mass spectrometry.

The majority of mitochondrial proteins are encoded in the nucleus, synthesized in the cytosol and imported into mitochondria mediated by an N-terminal mitochondrial targeting sequences (MTS). After import, the MTS is cleaved off by the mitochondrial processing peptidase (MPP) and subsets of the imported proteins are further processed by the aminopeptidase intermediate cleaving peptidase 55 (ICP55), the mitochondrial intermediate peptidase (MIP), octapeptidyl aminopeptidase 1 (Oct1) or other proteolytic enzymes. Mutations that impair the mitochondrial processing machinery or mitochondrial protein degradation result in rare but severe human diseases. In addition, aging and various stress conditions are associated with altered proteolysis of mitochondrial proteins. Enrichment of protein terminal peptides in combination with mass spectrometry-based identification and quantification has become the method of choice to study proteolytic processing. Here, we describe an updated step-by-step protocol for the enrichment of N-terminal peptides by Hypersensitive Undecanal-mediated Enrichment of N-Terminal peptides (HUNTER). We describe analysis of mass spectrometry data acquired for HUNTER samples and present a suite of dedicated Python and R scripts for HUNTER quality control, classification of the enriched peptides, annotation of mitochondrial processing sites and quantitative evaluation. The scripts are freely available at https://github.com/FabianStockert/mito_annotation.

LineageFilter: Improved Proteotyping of Complex Samples Using Metaproteomics and Machine Learning.

Metaproteomics is a powerful tool to characterize how microbiota function by analyzing their proteic content by tandem mass spectrometry. Given the complexity of these samples, accurately assessing their taxonomical composition without prior information based solely on peptide sequences remains a challenge. Here, we present LineageFilter, a new python-based AI software for refined proteotyping of complex samples using metaproteomics interpreted data and machine learning. Given a tentative list of taxa, their abundances, and the scores associated with their identified peptides, LineageFilter computes a comprehensive set of features for each identified taxon at all taxonomical ranks. Its machine-learning model then assesses the likelihood of each taxon's presence based on these features, enabling improved proteotyping and sample-specific database construction.

Thermal Denaturation of Fresh Frozen Tissue Enhances Mass Spectrometry Detection of Peptides.

Thermal denaturation (TD), known as antigen retrieval, heats tissue samples in a buffered solution to expose protein epitopes. Thermal denaturation of formalin-fixed paraffin-embedded samples enhances on-tissue tryptic digestion, increasing peptide detection using matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS). We investigated the tissue-dependent effects of TD on peptide MALDI IMS and liquid chromatography-tandem mass spectrometry signal in unfixed, frozen human colon, ovary, and pancreas tissue. In a triplicate experiment using time-of-flight, orbitrap, and Fourier-transform ion cyclotron resonance mass spectrometry platforms, we found that TD had a tissue-dependent effect on peptide signal, resulting in a (22.5%) improvement in peptide detection from the colon, a (73.3%) improvement in ovary tissue, and a (96.6%) improvement in pancreas tissue. Biochemical analysis of identified peptides shows that TD facilitates identification of hydrophobic peptides.

An optimised method to isotopically label pure synthetic peptides 'in-house' for absolute quantification in bottom-up proteomics.

RATIONALE: Heavy-labelled internal standards increasingly represent the gold standard for absolute quantitation in mass spectrometry (MS)-based bottom-up proteomics. The biggest drawbacks of using these standards are that they have high costs and lengthy lead times. METHODS: We describe an efficient, low-cost optimised method to enable 'in-house' heavy labelling of synthetic tryptic peptides for absolute quantification using tandem LC-MS/MS mass spectrometry. Our methodology uses 18O water in a trypsin-catalysed oxygen exchange reaction at the carboxyl terminus with the overall aim of reducing the costs and lead time associated with sourcing heavy standards from commercial vendors. RESULTS: Step-by-step instructions are provided on how to execute this protocol with high-throughput adaptations utilising a 96-well plate and a liquid-handling robot. Detailed notes on experimental setup, tips for troubleshooting and suggested improvements to maximise labelling efficiencies are highlighted to achieve the best results. Under optimum conditions, labelling efficiencies of peptides can reach from 95% to 100%. CONCLUSIONS: The application of the 'in-house' labelled standards in generating calibration curves to quantify endogenous peptide concentrations is just as effective as using the synthetically sourced standards while also having great cost reduction implications as well as saving time spent waiting for peptides to arrive. The protocol is highly adaptable and can be customized to fit the specific setup of any laboratory, maximizing achievable labelling efficiencies.

Bioactive peptides from Tenebrio molitor: physicochemical and antioxidant properties and antimicrobial capacity.

Recent research has demonstrated the increasing interest in using insects for the extraction of bioactive compounds, particularly peptides. These compounds offer a spectrum of beneficial physiological effects. The aim of this study was to standardize a methodology for obtaining bioactive peptides from Tenebrio molitor and evaluate its physicochemical characterization, antioxidant, and antimicrobial potential. Six assays were carried out to hydrolyse larvae protein, with variations in Alcalase concentration (0.04 to 0.08%) and reaction time (3 to 8 h). The results indicated that the process applied to defatted mealworm flour was effective in reducing lipids by 82.5%. Consequently, it was an observed increase of 38.4% in protein content. Additionally, an increase in glycogen content was found in defatted mealworm flour (177 µmol glucose g-1 sample) and peptides (152.81 µmol glucose g-1 sample). The degree of hydrolysis was higher in assays with longer hydrolysis durations (8.14 - 8.38%). The antioxidant capacity was 12 to 14% lower in assays with an incubation time of 8h. In this sense, the methodology proposed in the present study proved to be efficient in obtaining bioactive peptides from T. molitor.

Theoretical Assessment of Indistinguishable Peptides in Mass Spectrometry-Based Proteomics.

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

Liquid Atmospheric Pressure Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Using a Commercial Ion Source and Orbitrap Mass Analyzer.

A liquid atmospheric pressure-matrix-assisted laser desorption/ionization (LAP-MALDI) method has been developed and applied to a commercial AP-MALDI source on a hybrid orbitrap mass analyzer. It is shown that electrospray ionization (ESI)-like mass spectra of a range of peptides and proteins can be acquired by LAP-MALDI mass spectrometry (MS) as previously demonstrated on a homemade LAP-MALDI-Q-TOF setup but without the need of any modification to the commercially available MS equipment used. Multiply charged peptide ions were recorded with a resolution of around 100,000 and a mass accuracy of less than 5 ppm. The higher resolution and mass accuracy of the orbitrap analyzer compared with previously employed Q-TOF instrumentation provided high confidence in bacterial proteoform and species identification by top-down protein analysis.

Influence of Software Settings on the Identification Rate, Quantification Results, and Reproducibility in Profiling Post-Translational Modifications by Microflow Liquid Chromatography-Ion Mobility-Quadrupole Time-Of-Flight Analysis Using PEAKS Software.

The influence of data evaluation parameters on qualitative and quantitative results of untargeted shotgun profiling of enzymatic and nonenzymatic post-translational modifications (PTMs) was investigated in a model of bovine whey protein α-lactalbumin heated with lactose. Based on the same raw data, individual adjustments to the protein database and enzyme settings of PEAKS studio software increased the identification rate from 27 unmodified peptides to 48 and from 322 peptides in total to 535. The qualitative and quantitative reproducibility was also assessed based on 18 measurements of one sample across three batches. A total of 570 peptides were detected. While 89 peptides were identified in all measurements, the majority of peptides (161) were detected only once and mostly based on nonindicative spectra. The reproducibility of label-free quantification (LFQ) in six measurements of the same sample was similar after processing the data by either the PTM algorithm or the LFQ algorithm. In both cases, about one-third of the peptides showed a coefficient of variation of above 20%. However, the LFQ algorithm increased the number of quantified peptides from 75 to 179. Data are available at the PRIDE Archive with the data set identifier PXD050363.

Revisiting Protein Reversed-Phase Chromatography for Bottom-Up Proteomics.

We revisited protein reversed-phase chromatography (RP), using state-of-the-art RP columns developed for biopharmaceuticals, such as monoclonal antibodies, in order to evaluate the suitability of this methodology as a prefractionation step for bottom-up proteomics. The protein RP prefractionation (Prot-RP) method was compared with two other widely used prefractionation methods, SDS-PAGE and high-pH peptide RP (Pept-RP) by using cell lysates as samples. The overlap between fractions of Prot-RP was comparable to that of SDS-PAGE, and the protein recovery was approximately 2-fold higher. On the other hand, the overlap between fractions of Prot-RP was slightly larger than that of Pept-RP, but Prot-RP was able to identify more protein termini and more isoform-specific peptides than Pept-RP. Our results indicate that the combination of highly efficient protein prefractionation with modern mass spectrometers is particularly effective for proteoform profiling from cellular samples.

Multi-step HPLC fractionation enabled in-depth and unbiased characterization of histone PTMs.

Histone post-translational modifications (PTMs) are critical epigenetic regulatory factors. Histone PTMs are highly dynamic and complicated, encompassing over 30 structurally diverse modifications across nearly 180 amino acid residues, which generated extensive information regarding histone marks. In proteomics-based characterization of histone PTMs, chemical derivatization and antibody-based affinity enrichment were frequently utilized to improve the identification depth. However, chemical derivatization suffered from the occurrence of side reactions, and antibody-based affinity enrichment focused on specific PTM types of interest. In this research, we developed a multi-step fractionation strategy for comprehensively unbiased detection of histone PTM sites. By combining protein-level fractionation with peptide-level alkaline and acid phase fractionation, we developed the Multidimensional Fractionation based Histone Mark Identification Technology (MudFIT) and increased PTM identification to a total of 264 histone PTM sites. To the best of our knowledge, this strategy achieved the most comprehensive characterization of histone PTM sites in a single proteomics study. Using the same starting amount of sample, MudFIT identified more Kac sites and Kac peptides than those in antibody-based acetylated peptide enrichment. Moreover, in addition to well-studied histone marks, we discovered 36 potential new histone PTM sites including H2BK116bu, H4R45me2, H1K63pr, and uncovered unknown histone PTM types like aminoadipic on lysine and nitrosylation on tyrosine. Our data provided a method and resource for in-depth characterization of histone PTM sites, facilitating further biological understanding of histone marks.

Investigation and Development of the BODIPY-Embedded Isotopic Signature for Chemoproteomics Labeling and Targeted Profiling.

A common goal in mass spectrometry-based chemoproteomics is to directly measure the site of conjugation between the target protein and the small molecule ligand. However, these experiments are inherently challenging due to the low abundance of labeled proteins and the difficulty in identifying modification sites using standard proteomics software. Reporter tags that either generate signature fragment ions or isotopically encode target peptides can be used for the preemptive discovery of labeled peptides even in the absence of identification. We investigated the potential of BODIPY FL azide as a click chemistry enabled chemoproteomics reagent due to the presence of boron and the unique 1:4 natural abundance ratio of 10B:11B. The isotopes of boron encode BODIPY-labeled peptides with a predictable pattern between the monoisotopic (M) and M+1 peaks. BODIPY-labeled peptides were identified in MS1 spectra using an R script that filters for the signature 10B:11B intensity ratio and mass defect. Application of the boron detection script resulted in three times the labeled peptide coverage achieved for a BODIPY-conjugated BSA sample compared with untargeted data-dependent acquisition sequencing. Furthermore, we used the inherent HF neutral loss signature from BODIPY to assist with BODIPY-modified peptide identification. Finally, we demonstrate the application of this approach using the BODIPY-conjugated BSA sample spiked into a complex E. coli. digest. In summary, our results show that the commercially available BODIPY FL azide clicked to alkyne-labeled peptides provides a unique isotopic signature for pinpointing the site(s) of modification with the added potential for on- or off-line UV or fluorescence detection.

Detection of gluten peptides in human duodenal fluids with immuno-liquid chromatography-mass spectrometry.

Gluten proteins are storage proteins in wheat that exhibit a certain resistance to gastrointestinal digestion. To explore solutions to cope with accidental ingestion of gluten in individuals suffering from gluten-related disorders, it is essential to monitor the fate of gluten peptides in biological samples, i.e., gastrointestinal juices, blood plasma or urine. In this work, we aimed at developing a mass spectrometry (MS)-based method for measuring gluten peptides in human duodenal fluids. Seven gluten peptides, including the well-documented 33-mer gluten peptide (LQLQPFPQPQLPYPQPQLPYPQPQLPYPQPQPF), were selected after a literature review and characterization of a gluten-containing product. Isotopically labelled peptides were used as references and a targeted liquid chromatography (LC) MS assay based on high resolution parallel reaction monitoring (PRM) was designed. Despite iterative and fine tuning of the LC-PRM-MS method, the low level of endogenous gluten peptides in human duodenal fluid samples precluded their direct detection. Thus, an initial immunoprecipitation (IP) step was included. Several antibodies were tested, and one proved reliable for the enrichment of the 33-mer gluten peptide as well as a few additional gluten peptides. Figures-of-merits of the immuno-LC-PRM-MS assay were assessed with a focus on quantification trueness and precision. We have developed an MS-based method for measuring the 33-mer gluten peptide in human duodenal fluids. Based on isotopic dilution, the method relies on the combination of IP and LC-PRM-MS analysis. Measurements were shown to be sensitive, quantitative, and reproducible.