Refinements of LC-MS/MS Spectral Counting Statistics Improve Quantification of Low Abundance Proteins

Proteomic Analysis of Surgery-induced Stress Post-Tracheal Transplantation Highlights Changes in Matrisome

OBJECTIVE

Investigate the impact of Surgery-induced stress (SIS) on the normal airway repair process after airway reconstruction using a mouse microsurgery model, mass spectrometry (MS), and bioinformatic analysis.

METHODS

Tracheal tissue from non-surgical (N = 3) and syngeneic tracheal grafts at 3 months post-replacement (N = 3) were assessed using mass spectrometry. Statistical analysis was done using MASCOT via Proteome Discoverer™. Proteins were categorized into total, dysregulated, suppressed, and evoked proteins in response to SIS. Dysregulated proteins were identified using cut-off values of -1 1 and t-test (p value <0.05). Enriched pathways were determined using STRING and Metascape.

RESULTS

At the three-month post-operation mark, we noted a significant increase in submucosal cellular infiltration (14343 ± 1286 cells/mm2, p = 0.0003), despite reduced overall thickness (30 ± 3 μm, p = 0.01), compared to Native (4578 ± 723 cells/mm2; 42 ± 6 μm). Matrisome composition remained preserved, with proteomic analysis identifying 193 commonly abundant proteins, encompassing 7.2% collagens, 34.2% Extracellular matrix (ECM) glycoproteins, 6.2% proteoglycans, 33.2% ECM regulators, 14.5% Extracellular matrix-affiliated, and 4.7% secreted factors. Additionally, our analysis unveiled a unique proteomic signature of 217 "Surgery-evoked proteins" associated with SIS, revealing intricate connections among neutrophils, ECM remodeling, and vascularization through matrix metalloproteinase-9 interaction.

CONCLUSIONS

Our study demonstrated the impact of SIS on the extracellular matrix, particularly MMP9, after airway reconstruction. The novel identification of MMP9 prompts further investigation into its potential role in repair.

LEVEL OF EVIDENCE

NA Laryngoscope, 134:4052-4059, 2024.

Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders

In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets.

Identification and characterization of plasma proteins associated with intra-amniotic inflammation and/or infection in women with preterm labor

This study aimed to identify plasma proteins that could serve as potential biomarkers for microbial invasion of the amniotic cavity (MIAC) or intra-amniotic inflammation (IAI) in women with preterm labor (PTL). A retrospective cohort comprised singleton pregnant women with PTL (24-34 weeks) who underwent amniocentesis. Pooled plasma samples were analyzed by label-free liquid chromatography-tandem mass spectrometry for proteome profiling in a nested case-control study (concomitant MIAC/IAI cases vs. non-MIAC/IAI controls [n = 10 per group]). Eight target proteins associated with MIAC/IAI were further verified by immunoassays in a large cohort (n = 230). Shotgun proteomic analysis revealed 133 differentially expressed proteins (fold change > 1.5, P < 0.05) in the plasma of MIAC/IAI cases. Further quantification confirmed that the levels of AFP were higher and those of kallistatin and TGFBI were lower in the plasma of women with MIAC and that the levels of kallistatin and TGFBI were lower in the plasma of women with IAI than in those without these conditions. The area under the curves of plasma AFP, kallistatin, and TGFBI ranged within 0.67-0.81 with respect to each endpoint. In summary, plasma AFP, kallistatin, and TGFBI may represent valuable non-invasive biomarkers for predicting MIAC or IAI in women with PTL.

Lateral interactions between CD276 and CD147 are essential for stemness in breast cancer: a novel insight from proximal proteome analysis

Oncogenic cell-surface membrane proteins contribute to the phenotypic and functional characteristics of cancer stem cells (CSCs). We employed a proximity-labeling proteomic approach to quantitatively analyze the cell-surface membrane proteins in close proximity to CD147 in CSCs. Furthermore, we compared CSCs to non-CSCs to identify CSC-specific cell-surface membrane proteins that are closely interact with CD147 and revealed that lateral interaction between CD147 and CD276 concealed within the lipid raft microdomain in CSCs, confers resistance to docetaxel, a commonly used chemotherapy agent for various cancer types, including metastatic breast cancer. Moreover, we investigated the clinical relevance of CD147 and CD276 co-expression in HER2+ breast cancer (BC) and triple-negative breast cancer patients who underwent chemotherapy. We observed poor disease-free survival and Overall survival rates in patients of CD147 and CD276 (p = 0.04 and 0.08, respectively). Subsequent immunohistochemical analysis in independent cohorts of HER2+ BC support for the association between co-expression of CD147 and CD276 and a poor response to chemotherapy. Collectively, our study suggests that the lateral interaction between CD147 and its proximal partners, such as CD276, may serve as a poor prognostic factor in BC and a predictive marker for the critical phenotypic determinant of BC stemness.

Mass spectrometry-based retina proteomics

A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.

Macular Edema in Central Retinal Vein Occlusion Correlates With Aqueous Fibrinogen Alpha Chain

Purpose

The global protein profile of the aqueous humor has been found to correlate with the severity of retinal vascular disease. Studying the aqueous humor in central retinal vein occlusion (CRVO) with proteomic techniques may bring insights to the molecular mechanisms underlying the condition.

Methods

Aqueous humor samples from treatment naïve patients with CRVO complicated by macular edema (n = 28) and age-matched controls (n = 20) were analyzed by label-free quantification liquid chromatography - tandem mass spectrometry. Best corrected visual acuity (BCVA) was measured as logMAR, and the severity of macular edema was evaluated as central retinal thickness (CRT) with optical coherence tomography. Control samples were obtained prior to cataract surgery. Significantly changed proteins were identified by a permutation-based calculation with a false discovery rate of 0.05.

Results

A total of 177 proteins were differentially expressed in CRVO. Regulated proteins were involved in complement activation, innate immune response, blood coagulation, and cell adhesion. Upregulated proteins that correlated with BCVA and CRT included fibrinogen alpha, beta, and gamma chains, fibronectin, Ig lambda-6 chain C region, Ig alpha-1 chain C region, and complement C7. Downregulated proteins that correlated negatively with BCVA, and CRT, included procollagen C-endopeptidase enhancer 1, clusterin, opticin, reelin, fibrillin-1, and cadherin-2. Monocyte differentiation antigen CD14 and lipopolysaccharide-binding protein were increased in CRVO.

Conclusions

Fibrinogen chains, fibronectin, and immunoglobulin components correlated with BCVA and CRT, suggesting a multifactorial response. Protective anti-angiogenic proteins, including procollagen C-endopeptidase enhancer 1, clusterin, and opticin, were downregulated in CRVO and correlated negatively with BCVA and CRT.

Challenges in neoantigen-directed therapeutics

A fundamental prerequisite for the efficacy of cancer immunotherapy is the presence of functional, antigen-specific T cells within the tumor. Neoantigen-directed therapy is a promising strategy that aims at targeting the host's immune response against tumor-specific antigens, thereby eradicating cancer cells. Initial forays have been made in clinical environments utilizing vaccines and adoptive cell therapy; however, many challenges lie ahead. We provide an in-depth overview of the current state of the field with an emphasis on in silico neoantigen discovery and the clinical aspects that need to be addressed to unlock the full potential of this therapy.

Merkel cell polyomavirus small T antigen is a viral transcription activator that is essential for viral genome maintenance

Merkel cell polyomavirus (MCV) is a small DNA tumor virus that persists in human skin and causes Merkel cell carcinoma (MCC) in immunocompromised individuals. The multi-functional protein MCV small T (sT) activates viral DNA replication by stabilizing large T (LT) and promotes cell transformation through the LT stabilization domain (LTSD). Using MCVΔsT, a mutant MCV clone that ablates sT, we investigated the role of sT in MCV genome maintenance. sT was dispensable for initiation of viral DNA replication, but essential for maintenance of the MCV genome and activation of viral early and late gene expression for progression of the viral lifecycle. Furthermore, in phenotype rescue studies, exogenous sT activated viral DNA replication and mRNA expression in MCVΔsT through the LTSD. While exogenous LT expression, which mimics LT stabilization, increased viral DNA replication, it did not activate viral mRNA expression. After cataloging transcriptional regulator proteins by proximity-based MCV sT-host protein interaction analysis, we validated LTSD-dependent sT interaction with four transcriptional regulators: Cux1, c-Jun, BRD9, and CBP. Functional studies revealed Cux1 and c-Jun as negative regulators, and CBP and BRD9 as positive regulators of MCV transcription. CBP inhibitor A-485 suppressed sT-induced viral gene activation in replicating MCVΔsT and inhibited early gene expression in MCV-integrated MCC cells. These results suggest that sT promotes viral lifecycle progression by activating mRNA expression and capsid protein production through interaction with the transcriptional regulators. This activity is essential for MCV genome maintenance, suggesting a critical role of sT in MCV persistence and MCC carcinogenesis.

Mass spectrometry and the cellular surfaceome

The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.

Non-targeted screening of pyranosides in Rhodiola crenulata using an all ion fragmentation-exact neutral loss strategy combined with liquid chromatography-quadrupole time-of-flight mass spectrometry

INTRODUCTION

Pyranosides as one kind of natural glycosides contain a pyran ring linked to an aglycone in the structure. They occur widely in plants and possess diverse biological activities. The discovery of new pyranosides not only contributes to research on natural products but also may promote pharmaceutical development.

OBJECTIVES

A non-targeted liquid chromatography-quadrupole time-of-flight mass spectrometry method coupled with an all ion fragmentation-exact neutral loss (AIF-ENL) strategy was developed for the screening of pyranosides in plants.

METHODS

Pyranosides in various types were collected as a model. The AIF-ENL strategy comprised three steps: AIF spectrum acquisition and generation, ENL-based searching and identification, and confirmation of structural type using target second-stage mass spectrometry (MS/MS). The strategy was systematically evaluated based on the matrix effects, fragmentation stability, scan rate and screening efficiency and finally applied to Rhodiola crenulata (Hook. f. et Thoms) H. Ohba.

RESULTS

The method was proved to be an efficient tool for the screening of pyranosides. When it was applied to R. crenulata, a total of 24 pyranoside candidates were detected. Among them, six were tentatively identified on the basis of the agreement of their elemental composition with the reported. The other 18 were detected in R. crenulata for the first time.

CONCLUSION

The method offers a new platform for discovering pyranosides. In addition, the developed non-targeted strategy can also be used for other natural products, such as flavonoids and coumarins, as long as there is a common fragmentation behaviour in their MS/MS to generate characteristic neutral losses or fragments.

Proteomic identification of novel plasma biomarkers associated with spontaneous preterm birth in women with preterm labor without infection/inflammation

Objective

We sought to identify plasma biomarkers associated with spontaneous preterm birth (SPTB, delivery within 21 days of sampling) in women with preterm labor (PTL) without intra-amniotic infection/inflammation (IAI) using label-free quantitative proteomic analysis, as well as to elucidate specific protein pathways involved in these cases.

Methods

This was a retrospective cohort study comprising 104 singleton pregnant women with PTL (24–32 weeks) who underwent amniocentesis and demonstrated no evidence of IAI. Analysis of pooled plasma samples collected from SPTB cases and term birth (TB) controls (n = 10 for each group) was performed using label-free quantitative mass spectrometry for proteome profiling in a nested case-control study design. Eight candidate proteins of interest were validated by ELISA-based assay and a clot-based assay in the total cohort.

Results

Ninety-one proteins were differentially expressed (P < 0.05) in plasma samples obtained from SPTB cases, of which 53 (58.2%) were upregulated and 38 (41.8%) were downregulated when compared to TD controls. A validation study confirmed that plasma from women who delivered spontaneously within 21 days of sampling contained significantly higher levels of coagulation factor Ⅴ and lower levels of S100 calcium binding protein A9 (S100A9), especially the former which was independent of baseline variables. The top-ranked pathways related to the 91 differentially expressed proteins were liver-X-receptor/retinoid X receptor (RXR) activation, acute phase response signaling, farnesoid X receptor/RXR activation, coagulation system, and complement system.

Conclusions

Proteomic analyses in this study identified potential novel biomarkers (i.e., coagulation factor V and S100A9) and potential protein pathways in plasma associated with SPTB in the absence of IAI in women with PTL. The present findings provide novel insights into the molecular pathogenesis and therapeutic targets specific for idiopathic SPTB.

Biochemical and Proteomic Characterization, and Pharmacological Insights of Indian Red Scorpion Venom Toxins

The Indian red scorpion (Mesobuthus tamulus) is one of the world's deadliest scorpions, with stings representing a life-threatening medical emergency. This species is distributed throughout the Indian sub-continent, including eastern Pakistan, eastern Nepal, and Sri Lanka. In India, Indian red scorpions are broadly distributed in western Maharashtra, Saurashtra, Kerala, Andhra Pradesh, Tamil Nadu, and Karnataka; however, fatal envenomations have been recorded primarily in the Konkan region of Maharashtra. The Indian red scorpion venom proteome comprises 110 proteins belonging to 13 venom protein families. The significant pharmacological activity is predominantly caused by the low molecular mass non-enzymatic Na+ and K+ ion channel toxins. Other minor toxins comprise 15.6% of the total venom proteome. Indian red scorpion stings induce the release of catecholamine, which leads to pathophysiological abnormalities in the victim. A strong correlation has been observed between venom proteome composition and local (swelling, redness, heat, and regional lymph node involvement) and systemic (tachycardia, mydriasis, hyperglycemia, hypertension, toxic myocarditis, cardiac failure, and pulmonary edema) manifestations. Immediate administration of antivenom is the preferred treatment for Indian red scorpion stings. However, scorpion-specific antivenoms have exhibited poor immunorecognition and neutralization of the low molecular mass toxins. The proteomic analysis also suggests that Indian red scorpion venom is a rich source of pharmacologically active molecules that may be envisaged as drug prototypes. The following review summarizes the progress made towards understanding the venom proteome of the Indian red scorpion and addresses the current understanding of the pathophysiology associated with its sting.

Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics

Analysis of differential abundance in proteomics data sets requires careful application of missing value imputation. Missing abundance values widely vary when performing comparisons across different sample treatments. For example, one would expect a consistent rate of “missing at random” (MAR) across batches of samples and varying rates of “missing not at random” (MNAR) depending on the inherent difference in sample treatments within the study. The missing value imputation strategy must thus be selected that best accounts for both MAR and MNAR simultaneously. Several important issues must be considered when deciding the appropriate missing value imputation strategy: (1) when it is appropriate to impute data; (2) how to choose a method that reflects the combinatorial manner of MAR and MNAR that occurs in an experiment. This paper provides an evaluation of missing value imputation strategies used in proteomics and presents a case for the use of hybrid left-censored missing value imputation approaches that can handle the MNAR problem common to proteomics data.

Heterogeneity in proline hydroxylation of fibrillar collagens observed by mass spectrometry

Collagen is the major protein in the extracellular matrix and plays vital roles in tissue development and function. Collagen is also one of the most processed proteins in its biosynthesis. The most prominent post-translational modification (PTM) of collagen is the hydroxylation of Pro residues in the Y-position of the characteristic (Gly-Xaa-Yaa) repeating amino acid sequence of a collagen triple helix. Recent studies using mass spectrometry (MS) and tandem MS sequencing (MS/MS) have revealed unexpected hydroxylation of Pro residues in the X-positions (X-Hyp). The newly identified X-Hyp residues appear to be highly heterogeneous in location and percent occupancy. In order to understand the dynamic nature of the new X-Hyps and their potential impact on applications of MS and MS/MS for collagen research, we sampled four different collagen samples using standard MS and MS/MS techniques. We found considerable variations in the degree of PTMs of the same collagen from different organisms and/or tissues. The rat tail tendon type I collagen is particularly variable in terms of both over-hydroxylation of Pro in the X-position and under-hydroxylation of Pro in the Y-position. In contrast, only a few unexpected PTMs in collagens type I and type III from human placenta were observed. Some observations are not reproducible between different sequencing efforts of the same sample, presumably due to a low population and/or the unpredictable nature of the ionization process. Additionally, despite the heterogeneous preparation and sourcing, collagen samples from commercial sources do not show elevated variations in PTMs compared to samples prepared from a single tissue and/or organism. These findings will contribute to the growing body of information regarding the PTMs of collagen by MS technology, and culminate to a more comprehensive understanding of the extent and the functional roles of the PTMs of collagen.

Mutual enlightenment: A toolbox of concepts and methods for integrating evolutionary and clinical toxinology via snake venomics and the contextual stance

Snakebite envenoming is a neglected tropical disease that may claim over 100,000 human lives annually worldwide. Snakebite occurs as the result of an interaction between a human and a snake that elicits either a defensive response from the snake or, more rarely, a feeding response as the result of mistaken identity. Snakebite envenoming is therefore a biological and, more specifically, an ecological problem. Snake venom itself is often described as a "cocktail", as it is a heterogenous mixture of molecules including the toxins (which are typically proteinaceous) responsible for the pathophysiological consequences of envenoming. The primary function of venom in snake ecology is pre-subjugation, with defensive deployment of the secretion typically considered a secondary function. The particular composition of any given venom cocktail is shaped by evolutionary forces that include phylogenetic constraints associated with the snake's lineage and adaptive responses to the snake's ecological context, including the taxa it preys upon and by which it is predated upon. In the present article, we describe how conceptual frameworks from ecology and evolutionary biology can enter into a mutually enlightening relationship with clinical toxinology by enabling the consideration of snakebite envenoming from an "ecological stance". We detail the insights that may emerge from such a perspective and highlight the ways in which the high-fidelity descriptive knowledge emerging from applications of -omics era technologies - "venomics" and "antivenomics" - can combine with evolutionary explanations to deliver a detailed understanding of this multifactorial health crisis.

Aqueous Fibronectin Correlates With Severity of Macular Edema and Visual Acuity in Patients With Branch Retinal Vein Occlusion: A Proteome Study

Purpose

Large-scale protein analysis may bring important insights into molecular changes following branch retinal vein occlusion (BRVO). Using proteomic techniques this study compared aqueous humor samples from patients with BRVO to age-matched controls.

Methods

Aqueous humor samples from treatment naive patients with BRVO complicated by macular edema (n = 19) and age-matched controls (n = 18) were analyzed with label-free quantification nano liquid chromatography - tandem mass spectrometry (LFQ nLC-MS/MS). The severity of macular edema was measured as central retinal thickness (CRT) with optical coherence tomography. Control samples were obtained prior to cataract surgery. Proteins were filtered by requiring quantification in at least 50% of the samples in each group without imputation of missing values. Significantly changed proteins were identified with a permutation-based calculation with a false discovery rate at 0.05.

Results

In BRVO, 52 proteins were differentially expressed. Regulated proteins were involved in cell adhesion, coagulation, and acute-phase response. Apolipoprotein C-III, complement C3, complement C5, complement factor H, fibronectin, and fibrinogen chains were increased in BRVO and correlated with CRT. Fibronectin also correlated with best corrected visual acuity (BCVA) and vascular endothelial growth factor (VEGF). Monocyte differentiation antigen CD14 (CD14) and lipopolysaccharide-binding protein (LBP) were upregulated in BRVO. Contactin-1 and alpha-enolase were downregulated in BRVO and correlated negatively with CRT.

Conclusions

Multiple proteins, including complement factors, fibrinogen chains, and apolipoprotein C-III, correlated with CRT, indicating a multifactorial response. Fibronectin correlated with BCVA, CRT, and VEGF. Fibronectin may reflect the severity of BRVO. The proinflammatory proteins CD14 and LBP were upregulated in BRVO.

Metabolomics bridging proteomics along metabolites/oncometabolites and protein modifications: Paving the way toward integrative multiomics

Systems biology adopted functional and integrative multiomics approaches enable to discover the whole set of interacting regulatory components such as genes, transcripts, proteins, metabolites, and metabolite dependent protein modifications. This interactome build up the midpoint of protein-protein/PTM, protein-DNA/RNA, and protein-metabolite network in a cell. As the key drivers in cellular metabolism, metabolites are precursors and regulators of protein post-translational modifications [PTMs] that affect protein diversity and functionality. The precisely orchestrated core pattern of metabolic networks refer to paradigm 'metabolites regulate PTMs, PTMs regulate enzymes, and enzymes modulate metabolites' through a multitude of feedback and feed-forward pathway loops. The concept represents a flawless PTM-metabolite-enzyme(protein) regulomics underlined in reprogramming cancer metabolism. Immense interconnectivity of those biomolecules in their spectacular network of intertwined metabolic pathways makes integrated proteomics and metabolomics an excellent opportunity, and the central component of integrative multiomics framework. It will therefore be of significant interest to integrate global proteome and PTM-based proteomics with metabolomics to achieve disease related altered levels of those molecules. Thereby, present update aims to highlight role and analysis of interacting metabolites/oncometabolites, and metabolite-regulated PTMs loop which may function as translational monitoring biomarkers along the reprogramming continuum of oncometabolism.

Integration of Data from Liquid-Liquid Phase Separation Databases Highlights Concentration and Dosage Sensitivity of LLPS Drivers

Liquid–liquid phase separation (LLPS) is a molecular process that leads to the formation of membraneless organelles, representing functionally specialized liquid-like cellular condensates formed by proteins and nucleic acids. Integrating the data on LLPS-associated proteins from dedicated databases revealed only modest agreement between them and yielded a high-confidence dataset of 89 human LLPS drivers. Analysis of the supporting evidence for our dataset uncovered a systematic and potentially concerning difference between protein concentrations used in a good fraction of the in vitro LLPS experiments, a key parameter that governs the phase behavior, and the proteomics-derived cellular abundance levels of the corresponding proteins. Closer scrutiny of the underlying experimental data enabled us to offer a sound rationale for this systematic difference, which draws on our current understanding of the cellular organization of the proteome and the LLPS process. In support of this rationale, we find that genes coding for our human LLPS drivers tend to be dosage-sensitive, suggesting that their cellular availability is tightly regulated to preserve their functional role in direct or indirect relation to condensate formation. Our analysis offers guideposts for increasing agreement between in vitro and in vivo studies, probing the roles of proteins in LLPS.

Different Research Approaches in Unraveling the Venom Proteome of Naja ashei

The dynamic development of venomics in recent years has resulted in a significant increase in publicly available proteomic data. The information contained therein is often used for comparisons between different datasets and to draw biological conclusions therefrom. In this article, we aimed to show the possible differences that can arise, in the final results of the proteomic experiment, while using different research workflows. We applied two software solutions (PeptideShaker and MaxQuant) to process data from shotgun LC-MS/MS analysis of Naja ashei venom and collate it with the previous report concerning this species. We were able to provide new information regarding the protein composition of this venom but also present the qualitative and quantitative limitations of currently used proteomic methods. Moreover, we reported a rapid and straightforward technique for the separation of the fraction of proteins from the three-finger toxin family. Our results underline the necessary caution in the interpretation of data based on a comparative analysis of data derived from different studies.

New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease

Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation. Here, we propose new Complexity Based Normalization (CBN) methods that introduced a variable adjustment factor (f), related to the complexity of the sample, both in terms of total number of identified proteins (CBN(P)) and as total number of spectral counts (CBN(S)). Both these new methods were compared with the Normalized Spectral Abundance Factor (NSAF) and the Spectral Counts log Ratio (Rsc), by using standard protein mixtures. Finally, to test the robustness and the effectiveness of the CBNs methods, they were employed for the comparative analysis of cortical protein extract from zQ175 mouse brains, model of Huntington Disease (HD), and control animals (raw data available via ProteomeXchange with identifier PXD017471). LF data were also validated by western blot and MRM based experiments. On standard mixtures, both CBN methods showed an excellent behavior in terms of reproducibility and coefficients of variation (CVs) in comparison to the other SpCs approaches. Overall, the CBN(P) method was demonstrated to be the most reliable and sensitive in detecting small differences in protein amounts when applied to biological samples.

PeptideWitch-A Software Package to Produce High-Stringency Proteomics Data Visualizations from Label-Free Shotgun Proteomics Data

PeptideWitch is a python-based web module that introduces several key graphical and technical improvements to the Scrappy software platform, which is designed for label-free quantitative shotgun proteomics analysis using normalised spectral abundance factors. The program inputs are low stringency protein identification lists output from peptide-to-spectrum matching search engines for ‘control’ and ‘treated’ samples. Through a combination of spectral count summation and inner joins, PeptideWitch processes low stringency data, and outputs high stringency data that are suitable for downstream quantitation. Data quality metrics are generated, and a series of statistical analyses and graphical representations are presented, aimed at defining and presenting the difference between the two sample proteomes.