Estimation of absolute protein quantities of unlabeled samples by selected reaction monitoring mass spectrometry

Enhanced protein extraction and quantification protocol for microsamples: An ultra-sensitive workflow for low-volume, low-concentration total protein lysates

Accurate protein quantification at low concentrations and small volumes is critical for advancing small-scale research, such as microvasculature studies. However, existing microscale protocols often require ≥5 μL of sample or highly concentrated lysates, limiting their applicability in contexts with scarce material. To overcome these limitations, we developed the Nano-Extraction BCA-Optimized Workflow (NEBOW), a novel method requiring only 2 μL of sample and capable of detecting protein concentrations as low as 0.01 mg/mL. Optimized for the NanoDrop™ One UV-Vis Spectrophotometer, this workflow demonstrated significantly enhanced sensitivity and reproducibility compared to the standard BCA assay. Paired t tests (p < 0.01) and TOST equivalence testing (15% margin) confirmed key differences, with the NEBOW method producing steeper standard curves and more consistent results at low concentrations. Bland-Altman analysis showed that standard BCA tends to overestimate protein levels, while the NEBOW method maintained accuracy across a range of low-input samples. Western blot validation supported the improved performance of the new workflow. This approach offers a reliable, cost-effective solution for protein quantification when sample availability is limited, without sacrificing accuracy or sample integrity.

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Proteomic assay for rapid characterisation of Staphylococcus aureus antimicrobial resistance mechanisms directly from blood cultures

PURPOSE

Staphylococcus aureus is one of the most common pathogens causing bloodstream infection. A rapid characterisation of resistance to methicillin and, occasionally, to aminoglycosides for particular indications, is therefore crucial to quickly adapt the treatment and improve the clinical outcomes of septic patients. Among analytical technologies, targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as a promising tool to detect resistance mechanisms in clinical samples.

METHODS

A rapid proteomic method was developed to detect and quantify the most clinically relevant antimicrobial resistance effectors in S. aureus in the context of sepsis: PBP2a, PBP2c, APH(3')-III, ANT(4')-I, and AAC(6')-APH(2''), directly from positive blood cultures and in less than 70 min including a 30-min cefoxitin-induction step. The method was tested on spiked blood culture bottles inoculated with 124 S.aureus, accounting for the known genomic diversity of SCCmec types and the genetic background of the strains.

RESULTS

This method provided 99% agreement for PBP2a (n = 98/99 strains) detection. Agreement was 100% for PBP2c (n = 5/5), APH(3')-III (n = 16/16), and ANT(4')-I (n = 20/20), and 94% for AAC(6')-APH(2'') (n = 16/17). Across the entire strain collection, 100% negative agreement was reported for each of the 5 resistance proteins. Additionally, relative quantification of ANT(4')-I expression allowed to discriminate kanamycin-susceptible and -resistant strains, in all strains harbouring the ant(4')-Ia gene.

CONCLUSION

The LC-MS/MS method presented herein demonstrates its ability to provide a reliable determination of S. aureus resistance mechanisms, directly from positive blood cultures and in a short turnaround time, as required in clinical laboratories.

Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA

BACKGROUND

Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring.

METHODS

Here, we applied the recently co-developed hybrid-PRM/DIA technology as a new intelligent data acquisition strategy that allows for the comprehensive digitization of rare clinical samples at the proteotype level. Hybrid-PRM/DIA enables enhanced measurement sensitivity for a specific set of analytes of current clinical interest by the intelligent triggering of multiplexed parallel reaction monitoring (MSxPRM) in combination with the discovery-driven digitization of the clinical biospecimen using DIA. Heavy-labeled reference peptides were utilized as triggers for MSxPRM and monitoring of endogenous peptides.

RESULTS

We first evaluated hybrid-PRM/DIA in a clinical context on a pool of 185 selected proteotypic peptides for tumor-associated antigens derived from 64 annotated human protein groups. We demonstrated improved reproducibility and sensitivity for the detection of endogenous peptides, even at lower concentrations near the detection limit. Up to 179 MSxPRM scans were shown not to affect the overall DIA performance. Next, we applied hybrid-PRM/DIA for the integrated digitization of biobanked melanoma samples using a set of 30 AQUA peptides against 28 biomarker candidates with relevance in molecular tumor board evaluations of melanoma patients. Within the DIA-detected approximately 6500 protein groups, the selected marker candidates such as UFO, CDK4, NF1, and PMEL could be monitored consistently and quantitatively using MSxPRM scans, providing additional confidence for supporting future clinical decision-making.

CONCLUSIONS

Combining PRM and DIA measurements provides a new strategy for the sensitive and reproducible detection of protein markers from patients currently being discussed in molecular tumor boards in combination with the opportunity to discover new biomarker candidates.

Combined genomic-proteomic approach in the identification of Campylobacter coli amoxicillin-clavulanic acid resistance mechanism in clinical isolates

Introduction

Aminopenicillins resistance among Campylobacter jejuni and Campylobacter coli strains is associated with a single mutation in the promoting region of a chromosomal beta-lactamase blaOXA61, allowing its expression. Clavulanic acid is used to restore aminopenicillins activity in case of blaOXA61 expression and has also an inherent antimicrobial activity over Campylobacter spp. Resistance to amoxicillin-clavulanic acid is therefore extremely rare among these species: only 0.1% of all Campylobacter spp. analyzed in the French National Reference Center these last years (2017-2022).

Material and methods

Whole genome sequencing with bioinformatic resistance identification combined with mass spectrometry (MS) was used to identify amoxicillin-acid clavulanic resistance mechanism in Campylobacters.

Results

A G57T mutation in blaOXA61 promoting region was identified in all C. jejuni and C. coli ampicillin resistant isolates and no mutation in ampicillin susceptible isolates. Interestingly, three C. coli resistant to both ampicillin and amoxicillin-clavulanic acid displayed a supplemental deletion in the promoting region of blaOXA61 beta-lactamase, at position A69. Using MS, a significant difference in the expression of BlaOXA61 was observed between these three isolates and amoxicillin-clavulanic acid susceptible C. coli.

Conclusion

A combined genomics/proteomics approach allowed here to identify a rare putative resistance mechanism associated with amoxicillin-clavulanic acid resistance for C. coli.

Lifespan-extending interventions induce consistent patterns of fatty acid oxidation in mouse livers

Aging manifests as progressive deteriorations in homeostasis, requiring systems-level perspectives to investigate the gradual molecular dysregulation of underlying biological processes. Here, we report systemic changes in the molecular regulation of biological processes under multiple lifespan-extending interventions. Differential Rank Conservation (DIRAC) analyses of mouse liver proteomics and transcriptomics data show that mechanistically distinct lifespan-extending interventions (acarbose, 17α-estradiol, rapamycin, and calorie restriction) generally tighten the regulation of biological modules. These tightening patterns are similar across the interventions, particularly in processes such as fatty acid oxidation, immune response, and stress response. Differences in DIRAC patterns between proteins and transcripts highlight specific modules which may be tightened via augmented cap-independent translation. Moreover, the systemic shifts in fatty acid metabolism are supported through integrated analysis of liver transcriptomics data with a mouse genome-scale metabolic model. Our findings highlight the power of systems-level approaches for identifying and characterizing the biological processes involved in aging and longevity.

Small Open Reading Frame-Encoded Micro-Peptides: An Emerging Protein World

Small open reading frames (sORFs) are often overlooked features in genomes. In the past, they were labeled as noncoding or "transcriptional noise". However, accumulating evidence from recent years suggests that sORFs may be transcribed and translated to produce sORF-encoded polypeptides (SEPs) with less than 100 amino acids. The vigorous development of computational algorithms, ribosome profiling, and peptidome has facilitated the prediction and identification of many new SEPs. These SEPs were revealed to be involved in a wide range of basic biological processes, such as gene expression regulation, embryonic development, cellular metabolism, inflammation, and even carcinogenesis. To effectively understand the potential biological functions of SEPs, we discuss the history and development of the newly emerging research on sORFs and SEPs. In particular, we review a range of recently discovered bioinformatics tools for identifying, predicting, and validating SEPs as well as a variety of biochemical experiments for characterizing SEP functions. Lastly, this review underlines the challenges and future directions in identifying and validating sORFs and their encoded micropeptides, providing a significant reference for upcoming research on sORF-encoded peptides.

Targeted proteomics links virulence factor expression with clinical severity in staphylococcal pneumonia

Introduction

The bacterial pathogen Staphylococcus aureus harbors numerous virulence factors that impact infection severity. Beyond virulence gene presence or absence, the expression level of virulence proteins is known to vary across S. aureus lineages and isolates. However, the impact of expression level on severity is poorly understood due to the lack of high-throughput quantification methods of virulence proteins.

Methods

We present a targeted proteomic approach able to monitor 42 staphylococcal proteins in a single experiment. Using this approach, we compared the quantitative virulomes of 136 S. aureus isolates from a nationwide cohort of French patients with severe community-acquired staphylococcal pneumonia, all requiring intensive care. We used multivariable regression models adjusted for patient baseline health (Charlson comorbidity score) to identify the virulence factors whose in vitro expression level predicted pneumonia severity markers, namely leukopenia and hemoptysis, as well as patient survival.

Results

We found that leukopenia was predicted by higher expression of HlgB, Nuc, and Tsst-1 and lower expression of BlaI and HlgC, while hemoptysis was predicted by higher expression of BlaZ and HlgB and lower expression of HlgC. Strikingly, mortality was independently predicted in a dose-dependent fashion by a single phage-encoded virulence factor, the Panton-Valentine leucocidin (PVL), both in logistic (OR 1.28; 95%CI[1.02;1.60]) and survival (HR 1.15; 95%CI[1.02;1.30]) regression models.

Discussion

These findings demonstrate that the in vitro expression level of virulence factors can be correlated with infection severity using targeted proteomics, a method that may be adapted to other bacterial pathogens.

Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma

Mass spectrometry is a powerful technique for investigating renal pathologies and identifying biomarkers, and efficient protein extraction from kidney tissue is essential for bottom-up proteomic analyses. Detergent-based strategies aid cell lysis and protein solubilization but are poorly compatible with downstream protein digestion and liquid chromatography-coupled mass spectrometry, requiring additional purification and buffer-exchange steps. This study compares two well-established detergent-based methods for protein extraction (in-solution sodium deoxycholate (SDC); suspension trapping (S-Trap)) with the recently developed sample preparation by easy extraction and digestion (SPEED) method, which uses strong acid for denaturation. We compared the quantitative performance of each method using label-free mass spectrometry in both sheep kidney cortical tissue and plasma. In kidney tissue, SPEED quantified the most unique proteins (SPEED 1250; S-Trap 1202; SDC 1197). In plasma, S-Trap produced the most unique protein quantifications (S-Trap 150; SDC 148; SPEED 137). Protein quantifications were reproducible across biological replicates in both tissue (R2 = 0.85–0.90) and plasma (SPEED R2 = 0.84; SDC R2 = 0.76, S-Trap R2 = 0.65). Our data suggest SPEED as the optimal method for proteomic preparation in kidney tissue and S-Trap or SPEED as the optimal method for plasma, depending on whether a higher number of protein quantifications or greater reproducibility is desired.

Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum

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

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

Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures

A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.

A Practical Guide to Small Protein Discovery and Characterization Using Mass Spectrometry

Small proteins of up to ∼50 amino acids are an abundant class of biomolecules across all domains of life. Yet due to the challenges inherent in their size, they are often missed in genome annotations, and are difficult to identify and characterize using standard experimental approaches. Consequently, we still know few small proteins even in well-studied prokaryotic model organisms. Mass spectrometry (MS) has great potential for the discovery, validation, and functional characterization of small proteins. However, standard MS approaches are poorly suited to the identification of both known and novel small proteins due to limitations at each step of a typical proteomics workflow, i.e., sample preparation, protease digestion, liquid chromatography, MS data acquisition, and data analysis. Here, we outline the major MS-based workflows and bioinformatic pipelines used for small protein discovery and validation. Special emphasis is placed on highlighting the adjustments required to improve detection and data quality for small proteins. We discuss both the unbiased detection of small proteins and the targeted analysis of small proteins of interest. Finally, we provide guidelines to prioritize novel small proteins, and an outlook on methods with particular potential to further improve comprehensive discovery and characterization of small proteins.

Identifying Candidate Protein Markers of Acute Kidney Injury in Acute Decompensated Heart Failure

One-quarter of patients with acute decompensated heart failure (ADHF) experience acute kidney injury (AKI)—an abrupt reduction or loss of kidney function associated with increased long-term mortality. There is a critical need to identify early and real-time markers of AKI in ADHF; however, to date, no protein biomarkers have exhibited sufficient diagnostic or prognostic performance for widespread clinical uptake. We aimed to identify novel protein biomarkers of AKI associated with ADHF by quantifying changes in protein abundance in the kidneys that occur during ADHF development and recovery in an ovine model. Relative quantitative protein profiling was performed using sequential window acquisition of all theoretical fragment ion spectra–mass spectrometry (SWATH–MS) in kidney cortices from control sheep (n = 5), sheep with established rapid-pacing-induced ADHF (n = 8), and sheep after ~4 weeks recovery from ADHF (n = 7). Of the 790 proteins quantified, we identified 17 candidate kidney injury markers in ADHF, 1 potential kidney marker of ADHF recovery, and 2 potential markers of long-term renal impairment (differential abundance between groups of 1.2–2.6-fold, adjusted p < 0.05). Among these 20 candidate protein markers of kidney injury were 6 candidates supported by existing evidence and 14 novel candidates not previously implicated in AKI. Proteins of differential abundance were enriched in pro-inflammatory signalling pathways: glycoprotein VI (activated during ADHF development; adjusted p < 0.01) and acute phase response (repressed during recovery from ADHF; adjusted p < 0.01). New biomarkers for the early detection of AKI in ADHF may help us to evaluate effective treatment strategies to prevent mortality and improve outcomes for patients.

Long noncoding RNA and protein abundance in lncRNPs

Although long noncoding RNAs (lncRNAs) are generally expressed at low levels, emerging evidence has revealed that many play important roles in gene regulation by a variety of mechanisms as they engage with proteins. Given that the abundance of proteins often greatly exceeds that of their interacting lncRNAs, quantification of the relative abundance, or even the exact stoichiometry in some cases, within lncRNA-protein complexes is helpful for understanding of the mechanism(s) of action of lncRNAs. We discuss methods used to examine lncRNA and protein expression at the single cell, subcellular, and suborganelle levels, the average and local lncRNA concentration in cells, as well as how lncRNAs can modulate the functions of their interacting proteins even at a low stoichiometric concentration.

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.

From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions

Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non-metabolic stresses, and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of large-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.

An innovative standard for LC-MS-based HCP profiling and accurate quantity assessment: Application to batch consistency in viral vaccine samples

Biotherapeutics, molecules produced from biological systems, require rigorous purification steps to remove impurities including host cell proteins (HCPs). Regulatory guidelines require manufacturers to monitor process-related impurities along the purification workflow. Mass spectrometry (MS) has recently been considered as a complementary method to the well-established ELISA for HCPs quantification, since it has the advantage of unambiguously identifying individual HCP. In this study, we developed an innovative standard dedicated to MS-based HCP profiling analysis in order to monitor the consistency of viral vaccine intermediate purification samples. This standard, termed the HCP-PROFILER standard, is composed of a water-soluble bead (READYBEADS technology) which, after being added into the sample, releases unlabeled peptides in controlled amounts. The standard meets three desired criteria: (1) it is composed of multiple peptides, at different concentration levels, allowing construction of a calibration curve covering the dynamic range of HCPs present in the target sample, ensuring quantification accuracy; (2) it demonstrates high batch-to-batch reproducibility, ensuring quantification robustness and consistency over time; and (3) it is easy to use and avoids user-induced analytical biases. In this study, we present the use of the HCP-PROFILER standard for vaccine batches comparison and downstream process performance studies.

Mechanisms of Resistance to Ceftolozane/Tazobactam in Pseudomonas aeruginosa: Results of the GERPA Multicenter Study

Resistance mechanisms of Pseudomonas aeruginosa to ceftolozane/tazobactam (C/T) were assessed on a collection of 420 nonredundant strains nonsusceptible to ceftazidime (MIC > 8 μg/ml) and/or imipenem (>4 μg/ml), collected by 36 French hospital laboratories over a one-month period (the GERPA study). Rates of C/T resistance (MIC > 4/4 μg/ml) were equal to 10% in this population (42/420 strains), and 23.2% (26/112) among the isolates resistant to both ceftazidime and imipenem. A first group of 21 strains (50%) was found to harbor various extended-spectrum β-lactamases (1 OXA-14; 2 OXA-19; 1 OXA-35; 1 GES-9; and 3 PER-1), carbapenemases (2 GES-5; 1 IMP-8; and 8 VIM-2), or both (1 VIM-2/OXA-35 and 1 VIM-4/SHV-2a). All the strains of this group belonged to widely distributed epidemic clones (ST111, ST175, CC235, ST244, ST348, and ST654), and were highly resistant to almost all the antibiotics tested except colistin. A second group was composed of 16 (38%) isolates moderately resistant to C/T (MICs from 8/4 to 16/4 μg/ml), of which 7 were related to international clones (ST111, ST253, CC274, ST352, and ST386). As demonstrated by targeted mass spectrometry, cloxacillin-based inhibition tests, and gene bla _PDC deletion experiments, this resistance phenotype was correlated with an extremely high production of cephalosporinase PDC. In part accounting for this strong PDC upregulation, genomic analyses revealed the presence of mutations in the regulator AmpR (D135N/G in 6 strains) and enzymes of the peptidoglycan recycling pathway, such as AmpD, PBP4, and Mpl (9 strains). Finally, all of the 5 (12%) remaining C/T-resistant strains (group 3) appeared to encode PDC variants with mutations known to improve the hydrolytic activity of the β-lactamase toward ceftazidime and C/T (F147L, ΔL223-Y226, E247K, and N373I). Collectively, our results highlight the importance of both intrinsic and transferable mechanisms in C/T-resistant P. aeruginosa Which mutational events lead some clinical strains to massively produce the natural cephalosporinase PDC remains incompletely understood.

Deadly Proteomes: A Practical Guide to Proteotranscriptomics of Animal Venoms

Animal venoms are renowned for their toxicity, biochemical complexity, and as a source of compounds with potential applications in medicine, agriculture, and industry. Polypeptides underlie much of the pharmacology of animal venoms, and elucidating these arsenals of polypeptide toxins-known as the venom proteome or venome-is an important step in venom research. Proteomics is used for the identification of venom toxins, determination of their primary structure including post-translational modifications, as well as investigations into the physiology underlying their production and delivery. Advances in proteomics and adjacent technologies has led to a recent upsurge in publications reporting venom proteomes. Improved mass spectrometers, better proteomic workflows, and the integration of next-generation sequencing of venom-gland transcriptomes and venomous animal genomes allow quicker and more accurate profiling of venom proteomes with greatly reduced starting material. Technologies such as imaging mass spectrometry are revealing additional insights into the mechanism, location, and kinetics of venom toxin production. However, these numerous new developments may be overwhelming for researchers designing venom proteome studies. Here, the field of venom proteomics is reviewed and some practical solutions for simplifying mass spectrometry workflows to study animal venoms are offered.

Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis

Dynamic cellular processes such as differentiation are driven by changes in the abundances of transcription factors (TFs). However, despite years of studies, our knowledge about the protein copy number of TFs in the nucleus is limited. Here, by determining the absolute abundances of 103 TFs and co-factors during the course of human erythropoiesis, we provide a dynamic and quantitative scale for TFs in the nucleus. Furthermore, we establish the first gene regulatory network of cell fate commitment that integrates temporal protein stoichiometry data with mRNA measurements. The model revealed quantitative imbalances in TFs' cross-antagonistic relationships that underlie lineage determination. Finally, we made the surprising discovery that, in the nucleus, co-repressors are dramatically more abundant than co-activators at the protein level, but not at the RNA level, with profound implications for understanding transcriptional regulation. These analyses provide a unique quantitative framework to understand transcriptional regulation of cell differentiation in a dynamic context.

Germ-free and microbiota-associated mice yield small intestinal epithelial organoids with equivalent and robust transcriptome/proteome expression phenotypes

Intestinal epithelial organoids established from gut tissue have become a widely used research tool. However, it remains unclear how environmental cues, divergent microbiota composition and other sources of variation before, during and after establishment confound organoid properties, and how these properties relate to the original tissue. While environmental influences cannot be easily addressed in human organoids, mice offer a controlled assay-system. Here, we probed the effect of donor microbiota differences, previously identified as a confounding factor in murine in vivo studies, on organoids. We analysed the proteomes and transcriptomes of primary organoid cultures established from two colonised and one germ-free mouse colony of C57BL/6J genetic background, and compared them to their tissue of origin and commonly used cell lines. While an imprint of microbiota-exposure was observed on the proteome of epithelial samples, the long-term global impact of donor microbiota on organoid expression patterns was negligible. Instead, stochastic culture-to-culture differences accounted for a moderate variability between independently established organoids. Integration of transcriptome and proteome datasets revealed an organoid-typic expression signature comprising 14 transcripts and 10 proteins that distinguished organoids across all donors from murine epithelial cell lines and fibroblasts and closely mimicked expression patterns in the gut epithelium. This included the inflammasome components ASC, Naip1-6, Nlrc4 and Caspase-1, which were highly expressed in all organoids compared to the reference cell line m-ICc12 or mouse embryonic fibroblasts. Taken together, these results reveal that the donor microbiota has little effect on the organoid phenotype and suggest that organoids represent a more suitable culture model than immortalised cell lines, in particular for studies of intestinal epithelial inflammasomes.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Is It Possible to Find Needles in a Haystack? Meta-Analysis of 1000+ MS/MS Files Provided by the Russian Proteomic Consortium for Mining Missing Proteins

Despite direct or indirect efforts of the proteomic community, the fraction of blind spots on the protein map is still significant. Almost 11% of human genes encode missing proteins; the existence of which proteins is still in doubt. Apparently, proteomics has reached a stage when more attention and curiosity need to be exerted in the identification of every novel protein in order to expand the unusual types of biomaterials and/or conditions. It seems that we have exhausted the current conventional approaches to the discovery of missing proteins and may need to investigate alternatives. Here, we present an approach to deciphering missing proteins based on the use of non-standard methodological solutions and encompassing diverse MS/MS data, obtained for rare types of biological samples by members of the Russian Proteomic community in the last five years. These data were re-analyzed in a uniform manner by three search engines, which are part of the SearchGUI package. The study resulted in the identification of two missing and five uncertain proteins detected with two peptides. Moreover, 149 proteins were detected with a single proteotypic peptide. Finally, we analyzed the gene expression levels to suggest feasible targets for further validation of missing and uncertain protein observations, which will fully meet the requirements of the international consortium. The MS data are available on the ProteomeXchange platform (PXD014300).

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.

Recombinant expression, characterization, and quantification in human cancer cell lines of the Anaplastic Large-Cell Lymphoma-characteristic NPM-ALK fusion protein

Systemic anaplastic large cell lymphoma (ALCL) is an aggressive T-cell lymphoma most commonly seen in children and young adults. The majority of pediatric ALCLs are associated with the t(2;5)(p23;q35) translocation which fuses the Anaplastic Lymphoma Kinase (ALK) gene with the Nucleophosmin (NPM) gene. The NPM-ALK fusion protein is a constitutively-active tyrosine kinase, and plays a major role in tumor pathogenesis. In an effort to advance novel diagnostic approaches and the understanding of the function of this fusion protein in cancer cells, we expressed in E. coli, purified and characterized human NPM-ALK fusion protein to be used as a standard for estimating expression levels in cultured human ALCL cells, a key tool in ALCL pathobiology research. We estimated that NPM-ALK fusion protein is expressed at substantial levels in both Karpas 299 and SU-DHL-1 cells (ca. 4-6 million molecules or 0.5-0.7 pg protein per cell; based on our in-house developed NPM-ALK ELISA; LOD of 40 pM) as compared to the ubiquitous β-actin protein (ca. 64 million molecules or 4.5 pg per lymphocyte). We also compared NPM-ALK/ β-actin ratios determined by ELISA to those independently determined by two-dimensional electrophoresis and showed that the two methods are in good agreement.

Affinity-Bead Assisted Mass Spectrometry (Affi-BAMS): A Multiplexed Microarray Platform for Targeted Proteomics

The ability to quantitatively probe diverse panels of proteins and their post-translational modifications (PTMs) across multiple samples would aid a broad spectrum of biological, biochemical and pharmacological studies. We report a novel, microarray analytical technology that combines immuno-affinity capture with Matrix Assisted Laser Desorption Ionization Mass Spectrometry (MALDI MS), which is capable of supporting highly multiplexed, targeted proteomic assays. Termed "Affinity-Bead Assisted Mass Spectrometry" (Affi-BAMS), this LC-free technology enables development of highly specific and customizable assay panels for simultaneous profiling of multiple proteins and PTMs. While affinity beads have been used previously in combination with MS, the Affi-BAMS workflow uses enrichment on a single bead that contains one type of antibody, generally capturing a single analyte (protein or PTM) while having enough binding capacity to enable quantification within approximately 3 orders of magnitude. The multiplexing capability is achieved by combining Affi-BAMS beads with different protein specificities. To enable screening of bead-captured analytes by MS, we further developed a novel method of performing spatially localized elution of targets from individual beads arrayed on a microscope slide. The resulting arrays of micro spots contain highly concentrated analytes localized within 0.5 mm diameter spots that can be directly measured using MALDI MS. While both intact proteins and protein fragments can be monitored by Affi-BAMS, we initially focused on applying this technology for bottom-up proteomics to enable screening of hundreds of samples per day by combining the robust magnetic bead-based workflow with the high throughput nature of MALDI MS acquisition. To demonstrate the variety of applications and robustness of Affi-BAMS, several studies are presented that focus on the response of 4EBP1, RPS6, ERK1/ERK2, mTOR, Histone H3 and C-MET to stimuli including rapamycin, H2O2, EPO, SU11274, Staurosporine and Vorinostat.

Peptide mass mapping in bioapatites isolated from animal bones

Bioapatite ceramics produced from biogenic sources provide highly attractive materials for the preparation of artificial replacements since such materials are not only more easily accepted by living organisms, but bioapatite isolated from biowaste such as xenogeneous bones also provides a low-cost material. Nevertheless, the presence of organic compounds in the bioapatite may lead to a deterioration in its quality and may trigger an undesirable immune response. Therefore, procedures which ensure the elimination of organic compounds through bioapatite isolation are being subjected to intense investigation and the presence of remaining organic impurities is being determined through the application of various methods. Since current conclusions concerning the conditions suitable for the elimination of organic compounds remain ambiguous, we used the mass spectrometry-based proteomic approach in order to determine the presence of proteins or peptides in bioapatite samples treated under the most frequently employed conditions, i.e., the alkaline hydrothermal process and calcination at 500 °C. Since we also investigated the presence of proteins or peptides in treated bioapatite particles of differing sizes, we discovered that both calcination and the size of the bioapatite particles constitute the main factors influencing the presence of proteins or peptides in bioapatite. In fact, while intact proteins were detected even in calcinated bioapatite consisting of particles >250 µm, no proteins were detected in the same material consisting of particles <40 µm. Therefore, we recommend the use of powdered bioapatite for the preparation of artificial replacements since it is more effectively purified than apatite in the form of blocks. In addition, we observed that while alkaline hydrothermal treatment leads to the non-specific cleavage of proteins, it does not ensure the full degradation thereof.

A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS

Living systems integrate biochemical reactions that determine the functional state of each cell. Reactions are primarily mediated by proteins. In proteomic studies, these have been treated as independent entities, disregarding their higher-level organization into complexes that affects their activity and/or function and is thus of great interest for biological research. Here, we describe the implementation of an integrated technique to quantify cell-state-specific changes in the physical arrangement of protein complexes concurrently for thousands of proteins and hundreds of complexes. Applying this technique to a comparison of human cells in interphase and mitosis, we provide a systematic overview of mitotic proteome reorganization. The results recall key hallmarks of mitotic complex remodeling and suggest a model of nuclear pore complex disassembly, which we validate by orthogonal methods. To support the interpretation of quantitative SEC-SWATH-MS datasets, we extend the software CCprofiler and provide an interactive exploration tool, SECexplorer-cc.

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Global quantification of assembly state changes in the mitotic proteome

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Improved performance over thermostability measurement of proteome states

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Discovery of a mitotic disassembly intermediate of the nuclear pore complex

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Introduction of SECexplorer-cc, a publicly available online platform

Characterization and Relative Quantitation of Wheat, Rye, and Barley Gluten Protein Types by Liquid Chromatography-Tandem Mass Spectrometry

The consumption of wheat, rye, and barley may cause adverse reactions to wheat such as celiac disease, non-celiac gluten/wheat sensitivity, or wheat allergy. The storage proteins (gluten) are known as major triggers, but also other functional protein groups such as α-amylase/trypsin-inhibitors or enzymes are possibly harmful for people suffering of adverse reactions to wheat. Gluten is widely used as a collective term for the complex protein mixture of wheat, rye or barley and can be subdivided into the following gluten protein types (GPTs): α-gliadins, γ-gliadins, ω5-gliadins, ω1,2-gliadins, high- and low-molecular-weight glutenin subunits of wheat, ω-secalins, high-molecular-weight secalins, γ-75k-secalins and γ-40k-secalins of rye, and C-hordeins, γ-hordeins, B-hordeins, and D-hordeins of barley. GPTs isolated from the flours are useful as reference materials for clinical studies, diagnostics or in food analyses and to elucidate disease mechanisms. A combined strategy of protein separation according to solubility followed by preparative reversed-phase high-performance liquid chromatography was employed to purify the GPTs according to hydrophobicity. Due to the heterogeneity of gluten proteins and their partly polymeric nature, it is a challenge to obtain highly purified GPTs with only one protein group. Therefore, it is essential to characterize and identify the proteins and their proportions in each GPT. In this study, the complexity of gluten from wheat, rye, and barley was demonstrated by identification of the individual proteins employing an undirected proteomics strategy involving liquid chromatography-tandem mass spectrometry of tryptic and chymotryptic hydrolysates of the GPTs. Different protein groups were obtained and the relative composition of the GPTs was revealed. Multiple reaction monitoring liquid chromatography-tandem mass spectrometry was used for the relative quantitation of the most abundant gluten proteins. These analyses also allowed the identification of known wheat allergens and celiac disease-active peptides. Combined with functional assays, these findings may shed light on the mechanisms of gluten/wheat-related disorders and may be useful to characterize reference materials for analytical or diagnostic assays more precisely.

Missiles of Mass Disruption: Composition and Glandular Origin of Venom Used as a Projectile Defensive Weapon by the Assassin Bug Platymeris rhadamanthus

Assassin bugs (Reduviidae) produce venoms that are insecticidal, and which induce pain in predators, but the composition and function of their individual venom components is poorly understood. We report findings on the venom system of the red-spotted assassin bug Platymeris rhadamanthus, a large species of African origin that is unique in propelling venom as a projectile weapon when threatened. We performed RNA sequencing experiments on venom glands (separate transcriptomes of the posterior main gland, PMG, and the anterior main gland, AMG), and proteomic experiments on venom that was either defensively propelled or collected from the proboscis in response to electrostimulation. We resolved a venom proteome comprising 166 polypeptides. Both defensively propelled venom and most venom samples collected in response to electrostimulation show a protein profile similar to the predicted secretory products of the PMG, with a smaller contribution from the AMG. Pooled venom samples induce calcium influx via membrane lysis when applied to mammalian neuronal cells, consistent with their ability to cause pain when propelled into the eyes or mucus membranes of potential predators. The same venom induces rapid paralysis and death when injected into fruit flies. These data suggest that the cytolytic, insecticidal venom used by reduviids to capture prey is also a highly effective defensive weapon when propelled at predators.

A sensor kinase controls turgor-driven plant infection by the rice blast fungus

The blast fungus Magnaporthe oryzae gains entry to its host plant by means of a specialized pressure-generating infection cell called an appressorium, which physically ruptures the leaf cuticle^1,2. Turgor is applied as an enormous invasive force by septin-mediated reorganization of the cytoskeleton and actin-dependent protrusion of a rigid penetration hypha³. However, the molecular mechanisms that regulate the generation of turgor pressure during appressorium-mediated infection of plants remain poorly understood. Here we show that a turgor-sensing histidine-aspartate kinase, Sln1, enables the appressorium to sense when a critical turgor threshold has been reached and thereby facilitates host penetration. We found that the Sln1 sensor localizes to the appressorium pore in a pressure-dependent manner, which is consistent with the predictions of a mathematical model for plant infection. A Δsln1 mutant generates excess intracellular appressorium turgor, produces hyper-melanized non-functional appressoria and does not organize the septins and polarity determinants that are required for leaf infection. Sln1 acts in parallel with the protein kinase C cell-integrity pathway as a regulator of cAMP-dependent signalling by protein kinase A. Pkc1 phosphorylates the NADPH oxidase regulator NoxR and, collectively, these signalling pathways modulate appressorium turgor and trigger the generation of invasive force to cause blast disease.

Enhancing cardiac glycolysis causes an increase in PDK4 content in response to short-term high-fat diet

The healthy heart has a dynamic capacity to respond and adapt to changes in nutrient availability. Metabolic inflexibility, such as occurs with diabetes, increases cardiac reliance on fatty acids to meet energetic demands, and this results in deleterious effects, including mitochondrial dysfunction, that contribute to pathophysiology. Enhancing glucose usage may mitigate metabolic inflexibility and be advantageous under such conditions. Here, we sought to identify how mitochondrial function and cardiac metabolism are affected in a transgenic mouse model of enhanced cardiac glycolysis (Glyco^Hi) basally and following a short-term (7-day) high-fat diet (HFD). Glyco^Hi mice constitutively express an active form of phosphofructokinase-2, resulting in elevated levels of the PFK-1 allosteric activator fructose 2,6-bisphosphate. We report that basally Glyco^Hi mitochondria exhibit augmented pyruvate-supported respiration relative to fatty acids. Nevertheless, both WT and Glyco^Hi mitochondria had a similar shift toward increased rates of fatty acid-supported respiration following HFD. Metabolic profiling by GC-MS revealed distinct features based on both genotype and diet, with a unique increase in branched-chain amino acids in the Glyco^Hi HFD group. Targeted quantitative proteomics analysis also supported both genotype- and diet-dependent changes in protein expression and uncovered an enhanced expression of pyruvate dehydrogenase kinase 4 (PDK4) in the Glyco^Hi HFD group. These results support a newly identified mechanism whereby the levels of fructose 2,6-bisphosphate promote mitochondrial PDK4 levels and identify a secondary adaptive response that prevents excessive mitochondrial pyruvate oxidation when glycolysis is sustained after a high-fat dietary challenge.

A Review on Quantitative Multiplexed Proteomics

Over the last few decades, mass spectrometry-based proteomics has become an increasingly powerful tool that is now able to routinely detect and quantify thousands of proteins. A major advance for global protein quantification was the introduction of isobaric tags, which, in a single experiment, enabled the global quantification of proteins across multiple samples. Herein, these methods are referred to as multiplexed proteomics. The principles, advantages, and drawbacks of various multiplexed proteomics techniques are discussed and compared with alternative approaches. We also discuss how the emerging combination of multiplexing with targeted proteomics might enable the reliable and high-quality quantification of very low abundance proteins across multiple conditions. Lastly, we suggest that fusing multiplexed proteomics with data-independent acquisition approaches might enable the comparison of hundreds of different samples without missing values, while maintaining the superb measurement precision and accuracy obtainable with isobaric tag quantification.

Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate

Hematopoiesis provides an accessible system for studying the principles underlying cell-fate decisions in stem cells. Proposed models of hematopoiesis suggest that quantitative changes in lineage-specific transcription factors (LS-TFs) underlie cell-fate decisions. However, evidence for such models is lacking as TF levels are typically measured via RNA expression rather than by analyzing temporal changes in protein abundance. Here, we used single-cell mass cytometry and absolute quantification by mass spectrometry to capture the temporal dynamics of TF protein expression in individual cells during human erythropoiesis. We found that LS-TFs from alternate lineages are co-expressed, as proteins, in individual early progenitor cells and quantitative changes of LS-TFs occur gradually rather than abruptly to direct cell-fate decisions. Importantly, upregulation of a megakaryocytic TF in early progenitors is sufficient to deviate cells from an erythroid to a megakaryocyte trajectory, showing that quantitative changes in protein abundance of LS-TFs in progenitors can determine alternate cell fates.

Range size and growth temperature influence Eucalyptus species responses to an experimental heatwave

Understanding forest tree responses to climate warming and heatwaves is important for predicting changes in tree species diversity, forest C uptake, and vegetation-climate interactions. Yet, tree species differences in heatwave tolerance and their plasticity to growth temperature remain poorly understood. In this study, populations of four Eucalyptus species, two with large range sizes and two with comparatively small range sizes, were grown under two temperature treatments (cool and warm) before being exposed to an equivalent experimental heatwave. We tested whether the species with large and small range sizes differed in heatwave tolerance, and whether trees grown under warmer temperatures were more tolerant of heatwave conditions than trees grown under cooler temperatures. Visible heatwave damage was more common and severe in the species with small rather than large range sizes. In general, species that showed less tissue damage maintained higher stomatal conductance, lower leaf temperatures, larger increases in isoprene emissions, and less photosynthetic inhibition than species that showed more damage. Species exhibiting more severe visible damage had larger increases in heat shock proteins (HSPs) and respiratory thermotolerance (T_max ). Thus, across species, increases in HSPs and T_max were positively correlated, but inversely related to increases in isoprene emissions. Integration of leaf gas-exchange, isoprene emissions, proteomics, and respiratory thermotolerance measurements provided new insight into mechanisms underlying variability in tree species heatwave tolerance. Importantly, warm-grown seedlings were, surprisingly, more susceptible to heatwave damage than cool-grown seedlings, which could be associated with reduced enzyme concentrations in leaves. We conclude that species with restricted range sizes, along with trees growing under climate warming, may be more vulnerable to heatwaves of the future.

Multi-omic measurements of heterogeneity in HeLa cells across laboratories

Reproducibility in research can be compromised by both biological and technical variation, but most of the focus is on removing the latter. Here we investigate the effects of biological variation in HeLa cell lines using a systems-wide approach. We determine the degree of molecular and phenotypic variability across 14 stock HeLa samples from 13 international laboratories. We cultured cells in uniform conditions and profiled genome-wide copy numbers, mRNAs, proteins and protein turnover rates in each cell line. We discovered substantial heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto varieties, and observed progressive divergence within a specific cell line over 50 successive passages. Genomic variability has a complex, nonlinear effect on transcriptome, proteome and protein turnover profiles, and proteotype patterns explain the varying phenotypic response of different cell lines to Salmonella infection. These findings have implications for the interpretation and reproducibility of research results obtained from human cultured cells.

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

While mass spectrometry (MS)-based quantification of small molecules has been successfully used for decades, targeted MS has only recently been used by the proteomics community to investigate clinical questions such as biomarker verification and validation. Targeted MS holds the promise of a paradigm shift in the quantitative determination of proteins. Nevertheless, targeted quantitative proteomics requires improvisation in making sample processing, instruments, and data analysis more accessible. In the backdrop of the genomic era reaching its zenith, certain questions arise: is the proteomic era about to come? If we are at the beginning of a new future for protein quantification, are we prepared to incorporate targeted proteomics at the benchside for basic research and at the bedside for the good of patients? Here, an overview of the knowledge required to perform targeted proteomics as well as its applications is provided. A special emphasis is placed on upcoming areas such as peptidomics, proteoform research, and mass spectrometry imaging, where the utilization of targeted proteomics is expected to bring forth new avenues. The limitations associated with the acceptance of this technique for mainstream usage are also highlighted. Also see the video abstract here https://youtu.be/mieB47B8gZw.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Expression variation and covariation impair analog and enable binary signaling control

Due to noise in the synthesis and degradation of proteins, the concentrations of individual vertebrate signaling proteins were estimated to vary with a coefficient of variation (CV) of approximately 25% between cells. Such high variation is beneficial for population-level regulation of cell functions but abolishes accurate single-cell signal transmission. Here, we measure cell-to-cell variability of relative protein abundance using quantitative proteomics of individual Xenopus laevis eggs and cultured human cells and show that variation is typically much lower, in the range of 5-15%, compatible with accurate single-cell transmission. Focusing on bimodal ERK signaling, we show that variation and covariation in MEK and ERK expression improves controllability of the percentage of activated cells, demonstrating how variation and covariation in expression enables population-level control of binary cell-fate decisions. Together, our study argues for a control principle whereby low expression variation enables accurate control of analog single-cell signaling, while increased variation, covariation, and numbers of pathway components are required to widen the stimulus range over which external inputs regulate binary cell activation to enable precise control of the fraction of activated cells in a population.

The assassin bug Pristhesancus plagipennis produces two distinct venoms in separate gland lumens

The assassin bug venom system plays diverse roles in prey capture, defence and extra-oral digestion, but it is poorly characterised, partly due to its anatomical complexity. Here we demonstrate that this complexity results from numerous adaptations that enable assassin bugs to modulate the composition of their venom in a context-dependent manner. Gland reconstructions from multimodal imaging reveal three distinct venom gland lumens: the anterior main gland (AMG); posterior main gland (PMG); and accessory gland (AG). Transcriptomic and proteomic experiments demonstrate that the AMG and PMG produce and accumulate distinct sets of venom proteins and peptides. PMG venom, which can be elicited by electrostimulation, potently paralyses and kills prey insects. In contrast, AMG venom elicited by harassment does not paralyse prey insects, suggesting a defensive role. Our data suggest that assassin bugs produce offensive and defensive venoms in anatomically distinct glands, an evolutionary adaptation that, to our knowledge, has not been described for any other venomous animal.

Venom can be used both offensively for prey capture and defensively to deter predators. Here, Walker and colleagues demonstrate that the assassin bug Pristhesancus plagipennis has two distinct venom glands that produce venoms with distinct compositions that can be elicited by different stimuli.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Deciphering Multifactorial Resistance Phenotypes in Acinetobacter baumannii by Genomics and Targeted Label-free Proteomics

Resistance to β-lactams in Acinetobacter baumannii involves various mechanisms. To decipher them, whole genome sequencing (WGS) and real-time quantitative polymerase chain reaction (RT-qPCR) were complemented by mass spectrometry (MS) in selected reaction monitoring mode (SRM) in 39 clinical isolates. The targeted label-free proteomic approach enabled, in one hour and using a single method, the quantitative detection of 16 proteins associated with antibiotic resistance: eight acquired β-lactamases (i.e. GES, NDM-1, OXA-23, OXA-24, OXA-58, PER, TEM-1, and VEB), two resident β-lactamases (i.e. ADC and OXA-51-like) and six components of the two major efflux systems (i.e. AdeABC and AdeIJK). Results were normalized using "bacterial quantotypic peptides," i.e. peptide markers of the bacterial quantity, to obtain precise protein quantitation (on average 8.93% coefficient of variation for three biological replicates). This allowed to correlate the levels of resistance to β-lactam with those of the production of acquired as well as resident β-lactamases or of efflux systems. SRM detected enhanced ADC or OXA-51-like production and absence or increased efflux pump production. Precise protein quantitation was particularly valuable to detect resistance mechanisms mediated by regulated genes or by overexpression of chromosomal genes. Combination of WGS and MS, two orthogonal and complementary techniques, allows thereby interpretation of the resistance phenotypes at the molecular level.

Cardiac Insulin Signaling Regulates Glycolysis Through Phosphofructokinase 2 Content and Activity

BACKGROUND

The healthy heart has a dynamic capacity to respond and adapt to changes in nutrient availability. Diabetes mellitus disrupts this metabolic flexibility and promotes cardiomyopathy through mechanisms that are not completely understood. Phosphofructokinase 2 (PFK-2) is a primary regulator of cardiac glycolysis and substrate selection, yet its regulation under normal and pathological conditions is unknown. This study was undertaken to determine how changes in insulin signaling affect PFK-2 content, activity, and cardiac metabolism.

METHODS AND RESULTS

Streptozotocin-induced diabetes mellitus, high-fat diet feeding, and fasted mice were used to identify how decreased insulin signaling affects PFK-2 and cardiac metabolism. Primary adult cardiomyocytes were used to define the mechanisms that regulate PFK-2 degradation. Both type 1 diabetes mellitus and a high-fat diet induced a significant decrease in cardiac PFK-2 protein content without affecting its transcript levels. Overnight fasting also induced a decrease in PFK-2, suggesting it is rapidly degraded in the absence of insulin signaling. An unbiased metabolomic study demonstrated that decreased PFK-2 in fasted animals is accompanied by an increase in glycolytic intermediates upstream of phosphofructokianse-1, whereas those downstream are diminished. Mechanistic studies using cardiomyocytes showed that, in the absence of insulin signaling, PFK-2 is rapidly degraded via both proteasomal- and chaperone-mediated autophagy.

CONCLUSIONS

The loss of PFK-2 content as a result of reduced insulin signaling impairs the capacity to dynamically regulate glycolysis and elevates the levels of early glycolytic intermediates. Although this may be beneficial in the fasted state to conserve systemic glucose, it represents a pathological impairment in diabetes mellitus.

Absolute quantitation of disease protein biomarkers in a single LC-MS acquisition using apolipoprotein F as an example

LC-MS and immunoassay can detect protein biomarkers. Immunoassays are more commonly used but can potentially be outperformed by LC-MS. These techniques have limitations including the necessity to generate separate calibration curves for each biomarker. We present a rapid mass spectrometry-based assay utilising a universal calibration curve. For the first time we analyse clinical samples using the HeavyPeptide IGNIS kit which establishes a 6-point calibration curve and determines the biomarker concentration in a single LC-MS acquisition. IGNIS was tested using apolipoprotein F (APO-F), a potential biomarker for non-alcoholic fatty liver disease (NAFLD). Human serum and IGNIS prime peptides were digested and the IGNIS assay was used to quantify APO-F in clinical samples. Digestion of IGNIS prime peptides was optimised using trypsin and SMART Digest™. IGNIS was 9 times faster than the conventional LC-MS method for determining the concentration of APO-F in serum. APO-F decreased across NAFLD stages. Inter/intra-day variation and stability post sample preparation for one of the peptides was ≤13% coefficient of variation (CV). SMART Digest™ enabled complete digestion in 30 minutes compared to 24 hours using in-solution trypsin digestion. We have optimised the IGNIS kit to quantify APO-F as a NAFLD biomarker in serum using a single LC-MS acquisition.

Response induced in Mycoplasma gallisepticum under heat shock might be relevant to infection process

Despite the fact the term "proteome" was proposed to characterize a set of proteins in one of mycoplasma species, proteome response to various exposures in this bacteria are still obscure. Commonly, authors studying proteomic response on perturbation models in mycoplasmas use single approach and do not confirm their findings by alternative methods. Consequently, the results of proteomic analysis should be validated by complementary techniques. In this study we utilized three complementary approaches (SWATH, MRM, 2D-DIGE) to assess response of Mycoplasma gallisepticum under heat stress on proteomic level and combined these findings with metabolic response and the results of transcriptional profiling. We divide response into two modes - one is directly related to heat stress and other is triggered during heat stress, but not directly relevant to it. The latter includes accumulation of ATP and shedding of antigens. Both of these phenomena may be relevant to evasion of host's immune system and dissemination during mycoplasmosis in vivo.

A reporter system coupled with high-throughput sequencing unveils key bacterial transcription and translation determinants

Quantitative analysis of the sequence determinants of transcription and translation regulation is relevant for systems and synthetic biology. To identify these determinants, researchers have developed different methods of screening random libraries using fluorescent reporters or antibiotic resistance genes. Here, we have implemented a generic approach called ELM-seq (expression level monitoring by DNA methylation) that overcomes the technical limitations of such classic reporters. ELM-seq uses DamID (Escherichia coli DNA adenine methylase as a reporter coupled with methylation-sensitive restriction enzyme digestion and high-throughput sequencing) to enable in vivo quantitative analyses of upstream regulatory sequences. Using the genome-reduced bacterium Mycoplasma pneumoniae, we show that ELM-seq has a large dynamic range and causes minimal toxicity. We use ELM-seq to determine key sequences (known and putatively novel) of promoter and untranslated regions that influence transcription and translation efficiency. Applying ELM-seq to other organisms will help us to further understand gene expression and guide synthetic biology.

Quantitative analysis of how DNA sequence determines transcription and translation regulation is of interest to systems and synthetic biologists. Here the authors present ELM-seq, which uses Dam activity as reporter for high-throughput analysis of promoter and 5’-UTR regions.

Role of Type 2 NAD(P)H Dehydrogenase NdbC in Redox Regulation of Carbon Allocation in Synechocystis

NAD(P)H dehydrogenases comprise type 1 (NDH-1) and type 2 (NDH-2s) enzymes. Even though the NDH-1 complex is a well-characterized protein complex in the thylakoid membrane of Synechocystis sp. PCC 6803 (hereafter Synechocystis), the exact roles of different NDH-2s remain poorly understood. To elucidate this question, we studied the function of NdbC, one of the three NDH-2s in Synechocystis, by constructing a deletion mutant (ΔndbC) for a corresponding protein and submitting the mutant to physiological and biochemical characterization as well as to comprehensive proteomics analysis. We demonstrate that the deletion of NdbC, localized to the plasma membrane, affects several metabolic pathways in Synechocystis in autotrophic growth conditions without prominent effects on photosynthesis. Foremost, the deletion of NdbC leads, directly or indirectly, to compromised sugar catabolism, to glycogen accumulation, and to distorted cell division. Deficiencies in several sugar catabolic routes were supported by severe retardation of growth of the ΔndbC mutant under light-activated heterotrophic growth conditions but not under mixotrophy. Thus, NdbC has a significant function in regulating carbon allocation between storage and the biosynthesis pathways. In addition, the deletion of NdbC increases the amount of cyclic electron transfer, possibly via the NDH-12 complex, and decreases the expression of several transporters in ambient CO2 growth conditions.

A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability

Mutations truncating a single copy of the tumor suppressor, BRCA2, cause cancer susceptibility. In cells bearing such heterozygous mutations, we find that a cellular metabolite and ubiquitous environmental toxin, formaldehyde, stalls and destabilizes DNA replication forks, engendering structural chromosomal aberrations. Formaldehyde selectively depletes BRCA2 via proteasomal degradation, a mechanism of toxicity that affects very few additional cellular proteins. Heterozygous BRCA2 truncations, by lowering pre-existing BRCA2 expression, sensitize to BRCA2 haploinsufficiency induced by transient exposure to natural concentrations of formaldehyde. Acetaldehyde, an alcohol catabolite detoxified by ALDH2, precipitates similar effects. Ribonuclease H1 ameliorates replication fork instability and chromosomal aberrations provoked by aldehyde-induced BRCA2 haploinsufficiency, suggesting that BRCA2 inactivation triggers spontaneous mutagenesis during DNA replication via aberrant RNA-DNA hybrids (R-loops). These findings suggest a model wherein carcinogenesis in BRCA2 mutation carriers can be incited by compounds found pervasively in the environment and generated endogenously in certain tissues with implications for public health.