Label-free Proteome Quantification Research Articles

The sparing effect of ultra-high dose rate irradiation on the esophagus.

Current studies have substantiated the sparing effect of ultra-high dose rate irradiation (FLASH) in various organs including the brain, lungs, and intestines. Whether this sparing effect extends to esophageal tissue remains unexplored. This study aims to compare the different responses of esophageal tissue in histological and protein expression levels following conventional dose rate irradiation (CONV) and FLASH irradiation to ascertain the presence of a sparing effect. C57 female mice were randomly divided into three groups: control, CONV, and FLASH groups. The chest region of the mice in the radiation groups was exposed to a prescribed dose of 20 Gy using a modified electron linear accelerator. The CONV group received an average dose rate of 0.1 Gy/s, while the FLASH group received an average dose rate of 125 Gy/s. On the 10th day after irradiation, the mice were euthanized and their esophagi were collected for histopathological analysis. Subsequently, label-free proteomic quantification analysis was performed on esophageal tissue. The validation process involved analyzing transmission electron microscopy images and utilizing the parallel reaction monitoring method. Histopathology results indicated a significantly lower extent of esophageal tissue damage in the FLASH group compared to the CONV group (p < 0.05). Label-free quantitative proteomic analysis revealed that the sparing effect observed in the FLASH group may be attributed to a reduction in radiation-induced protein damage associated with mitochondrial functions, including proteins involved in the tricarboxylic acid cycle and oxidative phosphorylation, as well as a decrease in acute inflammatory responses. Compared with CONV irradiation, a sparing effect on esophageal tissue can be observed after FLASH irradiation. This sparing effect is associated with alleviated mitochondria damage and acute inflammation.

Proteomic analysis of stimulated saliva in gastroesophageal reflux disease patients with and without erosive tooth wear: Observational study

ObjectiveTo evaluate the difference in the proteomic profile of stimulated saliva in patients with gastroesophageal reflux disease (GERD) with (GE) and without (GNE) erosive tooth wear (ETW), regarding both human and bacterial proteins. MethodsStimulated saliva (SS) was collected from 16 patients (8/group). Samples were centrifuged at 4.500 g for 15 min under refrigeration to remove all debris. The supernatant from each saliva sample was taken and frozen at -80 °C. After extracting the proteins, they were submitted to reverse phase liquid chromatography and mass spectrometry (nLC-ESI-MS/MS). Label-free proteomic quantification was performed using Protein Lynx Global Service (PLGS) software (p < 0.05) for human and bacterial proteins. ResultsIn total, 67 human proteins were common for GNE and GE groups. GNE group presented, compared to GE group, increase in proteins that confer antimicrobial and acid resistant properties, such as cystatins, histatin and immunoglobulins. However, GNE group had a marked decrease in subunits of hemoglobin (α, β and delta). Regarding bacterial proteins, for SS, 7 and 10 unique proteins were identified in the GE and GNE groups, respectively. They are related to protein synthesis and energy metabolism and interact with human proteins typically found in saliva and supramolecular complexes of the acquired pellicle. ConclusionsOur data indicate that the stimulation of the salivary flow increases acid resistant and antimicrobial proteins in saliva, which might protect against ETW. Clinical significanceThis pioneer study showed important differences in the human and bacterial proteome of SS in patients with GERD with or without ETW.

Proteomic changes of the bilateral M1 and spinal cord in hemiplegic cerebral palsy mouse: Effects of constraint-induced movement therapy

Hemiplegic cerebral palsy (HCP) is a non-progressive movement and posture disorder that affects one side of the body. Constraint-induced movement therapy (CIMT) can improve the hand function of children with HCP. We used label-free proteomic quantification technology to evaluate proteomic changes in the bilateral M1 and spinal cord in HCP mouse induced by hypoxia/ischemia and CIMT. Nissl staining showed reduced neuron density in the HCP mice’s lesioned and contralesional M1. The rotarod test and grip strength test showed motor dysfunction in mice with HCP and improved motor ability after CIMT. A total of 5147 proteins were identified. Fifty-one, five, and sixty common differentially expressed proteins (DEPs), which were co-regulated by HCP and CIMT, were found in the lesioned M1, the contralesional M1 and the spinal cord respectively. The significant proteins included alpha-centractin, metaxin complex, PKC, septin 11, choline transporter-like proteins, protein 4.1, teneurin-4, and so on, which mainly related to synapse stability, neuronal development and maintenance, axon development, and myelin formation. The KEGG pathways of HCP-induced DEPs mainly related to lipid metabolism, synaptic remodeling, SNARE interactions in vesicular transport and axon formation. The CIMT-induced DEPs were mainly related to synaptic remodeling and axon formation in the lesioned M1 and spinal cord. This study investigated the proteomic changes of the bilateral M1 and spinal cord as well as the CIMT-induced proteomic changes in HCP mice, which might provide new insights into the therapy of HCP.

Insights concerning advancing the agroecological sustainability of salinity tolerance through proteomics profiling of hexaploid wheat (Triticum aestivum L.)

Wheat plays a significant role in the provision of food and nutrition. However, rapid soil salinization poses a severe threat to its production worldwide. Salt stress stunts wheat growth and quality, resulting in low grain yields. The adaptation of wheat to salinity involves complex physio-biochemical and molecular mechanisms. This study aimed to identify the genetic approaches concerning salt stress-responsive proteins and protein pathways in wheat roots under controlled (0 mM) and NaCl stress (250 mM) solution using label-free proteomic quantification analysis. We found a significant accumulation of Na+ in the leaf and root compared with the controlled condition. Besides, we identified 2436 proteins enhanced under salt stress, with 198 differentially abundant proteins (DAPs), including 170 up-regulated and 28 down-regulated proteins. Many of these proteins were involved in salinity tolerance, including heat shock proteins, glutathione S-transferase, dehydrin, peroxidase, potassium channel beta subunit-type H+-ATPase, superoxide dismutase (Cu-Zn), 14-3-3 protein, peroxidase, malate dehydrogenase, and heat shock proteins. The abundance of a V-type H+ ATPase and 14-3-3 protein was also enhanced, facilitating Na+ compartmentalization in the vacuole through the salt overly sensitive (SOS) pathway. Additionally, many antioxidant enzymes, including peroxidase, glutathione-S-transferase, and thioredoxins, were up-regulated, playing a vital role in detoxifying reactive oxygen species (ROS) in salinity-stressed wheat roots. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses showed that salinity stress enhances the abundance of proteins in several metabolic pathways, such as the citrate cycle, ribosome, oxidative phosphorylation, glycolysis, carbon metabolism, and cytoplasm. We anticipate that the identified proteins under salinity conditions will provide us with a deeper understanding of their application in agriculture biotechnology.

Metabolomics meets systems immunology.

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Label-free proteome quantification and evaluation.

The label-free quantification (LFQ) has emerged as an exceptional technique in proteomics owing to its broad proteome coverage, great dynamic ranges and enhanced analytical reproducibility. Due to the extreme difficulty lying in an in-depth quantification, the LFQ chains incorporating a variety of transformation, pretreatment and imputation methods are required and constructed. However, it remains challenging to determine the well-performing chain, owing to its strong dependence on the studied data and the diverse possibility of integrated chains. In this study, an R package EVALFQ was therefore constructed to enable a performance evaluation on >3000 LFQ chains. This package is unique in (a) automatically evaluating the performance using multiple criteria, (b) exploring the quantification accuracy based on spiking proteins and (c) discovering the well-performing chains by comprehensive assessment. All in all, because of its superiority in assessing from multiple perspectives and scanning among over 3000 chains, this package is expected to attract broad interests from the fields of proteomic quantification. The package is available at https://github.com/idrblab/EVALFQ.

Integrated multi-omic analyses on yellow Flammulina filiformis cultivar reveal postharvest oxidative damage responses

Yellow cultivars of Flammulina filiformis are prone to browning, which causes significant yearly loss. This study investigated the critical factors involved and revealed that oxygen plays an essential role in the browning process. Integrated multi-omic analyses, including genome sequencing, transcriptome profiling, and 4D label-free proteome quantification, were incorporated to dissect essential genes and metabolic pathways in the process of oxidative deterioration of the mushroom. The results revealed genes encoding browning-related enzymes in the F. filiformis genome, which are involved in the metabolism of tyrosine and the biosynthesis of phenylpropanoid. Laccase 4, which is over-regulated in oxygen-treated samples compared to anaerobically treated ones by transcriptomic and proteomic analysis, and further confirmed by qRT-PCR and enzyme assays, could be a crucial polyphenol oxidase catalyzing the browning reaction. DNA damaging, proteolysis, and oxidative phosphorylation accelerate cell senescence, contribute to cell integrity damage, and trigger the biosynthesis of melanin as a defective mechanism. These findings lay the foundations for postharvest preservation and future genetic breeding of F. filiformis.

IGF1R-IRS1/2 Pharmacological Inhibitors Act By Distinct Cellular and Molecular Mechanisms and Reveals Vulnerabilities for Treatment of Acute Myeloid Leukemia

Background: Preclinical rationale for targeting the insulin-like growth factor 1 (IGF1R)-Insulin Receptor Substrates 1 and 2 (IRS1/2) signaling in acute myeloid leukemia (AML), particularly in cells harboring the FLT3-ITD mutation, has been recently provided [Blood (2018) 132 Supp: 1512 and [Blood (2019) 134 Supp: 2689]. However, little is known about the non-canonical molecular mechanisms regulated by IGF1R-IRS1/2 signaling and pharmacological inhibition of this pathway in AML. Aims: To depict distinctive non-explicit molecular effects of linsitinib (IGF1R tyrosine kinase inhibitor) and NT157 (IGF1R-IRS1/2 allosteric inhibitor) treatment in FLT3-ITD-mutated AML cells. Material and methods: The MOLM-13 (homozygous) and MV4-11 (heterozygous) FLT3-ITD-mutated AML cell lines were treated with linsitinib (10 µM) or NT157 (1 µM) for 24 hours and used for label-free proteomic quantification analysis (n=3). Raw MS/MS data were processed using the SORCERER system and proteins were identified with built-in Andromeda search engine based on the human Uniprot proteome database. False discovery rate cutoffs were set to 1% on peptide, protein, and site decoy level, only allowing high quality identification to pass. Expression values were normalized across experimental conditions by quantile normalization based on the Limma-Voom pipeline, and then systematically compared similarities and differences in protein expression across experimental conditions by applying the Benjamin-Hochberg correction for multiple comparisons. To depict pathways associated to IGF1R, IRS1 and IRS2 gene expression related to processes identified by the proteomic data, we performed a gene-set enrichment analysis (GSEA) using the curated genesets for oncogenic events and molecular functions (MSigDB, Broad Institute) from RNA-seq data of the Cancer Genome Atlas AML cohort (n=173). Results: Considering a ≥ 2-fold change difference in both directions, linsitinib treatment downregulated 6 and 18 and upregulated 13 and 116 proteins in MOLM-13 and MV4-11 cells, respectively. Likewise, NT157 downregulated 12 and 126 and upregulated 204 and 297 proteins. When compared directly, linsitinib reduced expression of 11 and 35 and increased expression of 110 and 70 proteins in MOLM-13 and MV4-11 cells, respectively. Gene ontology identified that linsitinib resulted in upregulation of 7 molecular functions, while the NT157 ensued the upregulation of 18 and downregulation of 17 molecular functions pathways in a consistently manner between all comparisons. Of note, linsitinib activates post-transcriptional regulatory mechanisms, RNA metabolism (RNA binding P=1.15E-12; RNA processing P=8.64E-7) and reduced the protein and macromolecule metabolism (cellular protein metabolism P=3.86E-6). NT157 affected several of mitochondrial functions (increasing proton transmembrane transport activity P=1.55E-12, reducing oxidoreductase activity P=9.11E-10, and oxidative phosphorylation P=5.19E-8). Altogether, these data highlighted that NT157 profounder cytotoxic effect is a result of reprogramming of cellular energetics metabolism, and that linsitinib altered transcription and translation processes, probably as a result of autophagy, a mechanism originally described by our group [Blood (2017) 130 Supp: 3966]. GSEA analysis revealed that high IGF1R expression is positively enriched with RPS14 signature (Normalized Enriched Score [NES]=2.23; FDR-q<0.001), a ribosomal protein related to pathophysiology of myeloid neoplasms related to chromosome 5q deletion. Both IRS1 and IRS2 transcriptional signatures were associated with cellular growth signaling, such as AKT (NES=1.86; FDR-q= 0.006) and MYC (NES=1.67; FDR-q= 0.005), mitochondrial function [mitochondrial gene expression (NES=1.71; FDR-q= 0.001)]. Conclusion: Our proteomic data shed light on new and non-explicit mechanisms related to IGF1R-IRS1/2 inhibitors. Linsitinib modulates molecular processes related to RNA transcription and translation, while NT157 profoundly affect the cellular energetics, and, at least in part, explain the differential pre-clinical efficiency. Moreover, allosteric pharmacological inhibition of IGF1R-IRS1/2 pathway seems a more promising strategy than the tyrosine kinase inhibition, especially for AML subgroup more dependent of mitochondrial metabolism, such as AML with FLT3 mutation. DisclosuresNo relevant conflicts of interest to declare.

Kinetic analysis of effects of temperature and time on the regulation of venom expression in Bungarus multicinctus

Venom gland is a highly efficient venom production system to maintain their predatory arsenal. Venom toxins mRNA has been shown to increase abruptly in snake after venom expenditure, while the dynamics of venom accumulation during synthesis are poorly understood. Here, PacBio long-read sequencing, Illumina RNA sequencing (RNA-seq), and label-free proteome quantification were used to investigate the composition landscape and time- and temperature-dependent dynamics changes of the Bungarus multicinctus venom gland system. Transcriptome data (19.5223 Gb) from six adult B. multicinctus tissues were sequenced using PacBio RS II to generate a reference assembly, and average 7.28 Gb of clean RNA-seq data was obtained from venom glands by Illumina sequencing. Differentially expressed genes (DEGs) mainly were protein processing rather than venom toxins. Post-translational modifications provided the evidence of the significantly different proportions of toxins in the venom proteome with the changing of replenishment time and temperature, but constant of venom toxins mRNA in the venom gland transcriptome. Dynamic of toxins and genes involved in venom gland contraction suggesting the formation of the mature venom gland system would take at least 9 days. In addition, 59 toxin processing genes were identified, peptidylprolyl isomerase B of which underwent positive selection in Toxicofera. These results provide a reference for determining the extraction time of venom, production of polyclonal and monoclonal antibody for precise treatment plans of venomous snakebites, and construction of an in vitro synthesis system for snake venom protein.

Label-free proteomic quantification of packaged Flammulina filiformis during commercial storage

Abstract Fresh Flammulina filiformis is perishable and undergoes dynamic postharvest changes in physiological metabolism and biochemistry. In this study, we use label-free quantitative proteomics to elucidate the mechanisms of F. filiformis responses to cold storage and internal packaging stimuli. External quality including weight, browning, stipe elongation and cap opening were characterized during 21 d of commercial storage at 4 ℃. Among the 291 proteins identified from fresh and stored F. filiformis, we detected 39 upregulated and 73 downregulated differentially expressed proteins (DEPs). After 9 d of storage, 19 % of the upregulated DEPs were involved in the tricarboxylic acid (TCA) cycle, whereas 32 % of the downregulated DEPs were associated with translation. At the end of the storage period, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that most DEPs were involved in antibiotics biosynthesis, carbon metabolism and amino acid metabolites. Our results illuminate the biological processes occurring in F. filiformis under commercial storage conditions and provide a theoretical basis for the quality control of fresh F. filiformis.

Orthosiphon stamineus Proteins Alleviate Pentylenetetrazol-Induced Seizures in Zebrafish.

The anticonvulsive potential of proteins extracted from Orthosiphon stamineus leaves (OSLP) has never been elucidated in zebrafish (Danio rerio). This study thus aims to elucidate the anticonvulsive potential of OSLP in pentylenetetrazol (PTZ)-induced seizure model. Physical changes (seizure score and seizure onset time, behavior, locomotor) and neurotransmitter analysis were elucidated to assess the pharmacological activity. The protective mechanism of OSLP on brain was also studied using mass spectrometry-based label-free proteomic quantification (LFQ) and bioinformatics. OSLP was found to be safe up to 800 µg/kg and pre-treatment with OSLP (800 µg/kg, i.p., 30 min) decreased the frequency of convulsive activities (lower seizure score and prolonged seizure onset time), improved locomotor behaviors (reduced erratic swimming movements and bottom-dwelling habit), and lowered the excitatory neurotransmitter (glutamate). Pre-treatment with OSLP increased protein Complexin 2 (Cplx 2) expression in the zebrafish brain. Cplx2 is an important regulator in the trans-SNARE complex which is required during the vesicle priming phase in the calcium-dependent synaptic vesicle exocytosis. Findings in this study collectively suggests that OSLP could be regulating the release of neurotransmitters via calcium-dependent synaptic vesicle exocytosis mediated by the “Synaptic Vesicle Cycle” pathway. OSLP’s anticonvulsive actions could be acting differently from diazepam (DZP) and with that, it might not produce the similar cognitive insults such as DZP.

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling.

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major limitation is the potential performance drift of the LC-MS platform over time, which, in turn, limits its utility for analyzing large-scale sample sets. To address this, we introduce an experimental and data analysis scheme based on a block design with common references within each block for enabling large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller and more manageable blocks, minimizing instrument drift and variability within individual blocks. Each designated block also contains common reference samples (e.g., controls) for normalization across all blocks. We demonstrated the robustness of this approach by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. Following a common reference-based correction, 2537 proteins were quantified with high reproducibility without any imputation of missing values from 116 data sets. The data revealed the consistent quantification of proteins across all six blocks, as illustrated by the highly consistent abundances of house-keeping proteins in all samples and the high levels of correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

Comparative evaluation of label-free quantification strategies

The selection of a data processing method for use in mass spectrometry-based label-free proteome quantification contributes significantly to its accuracy and precision. In this study, we comprehensively evaluated 7 commonly-used label-free quantification methods (MaxQuant-Spectrum count, MaxQuant-iBAQ, MaxQuant-LFQ, MaxQuant-LFAQ, Proteome Discoverer, MetaMorpheus, TPP-StPeter) with a focus on missing values, precision, accuracy, selectivity, and reproducibility of low abundance protein quantification in both single shot and fractionation. Our results showed that among the tested strategies, MaxQuant in MaxLFQ mode outperformed other strategies in terms of accuracy and precision in both whole proteome and low abundance proteome quantification, whereas the Proteome Discoverer (PD) strategy using SEQUEST as a search engine performed better in terms of quantifiable low abundance proteome coverage. We subsequently applied the PD and MaxLFQ strategies in a blood proteomic dataset and found that many FDA-approved tumor prognostic biomarkers could be identified as well as quantified using the PD strategy, indicating the potential advantage of PD in label-free quantification studies. These results provide a reference for method choice in label-free quantification data analysis. SignificanceMass spectrometry-based label-free quantification methods play an important role in label-free proteome data analysis. In this study, we evaluated 7 commonly-used label-free quantification methods with respect to the following aspects: missing values, precision, accuracy, selectivity, and reproducibility for low abundance protein quantification. The results showed that, among the strategies evaluated, the PD strategy with SEQUEST as a search engine performed better in terms of low abundance protein coverage. This study provides a reference for method choice in label-free quantification data analysis.

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

Mass spectrometry-based spectral count has been a common choice of label-free proteome quantification due to the simplicity for the sample preparation and data generation. The discriminatory nature of spectral count in the MS data-dependent acquisition, however, inherently introduces the spectral count variation for low-abundance proteins in multiplicative LC-MS/MS analysis, which hampers sensitive proteome quantification. As many low-abundance proteins play important roles in cellular processes, deducing low-abundance proteins in a quantitatively reliable manner greatly expands the depth of biological insights. Here, we implemented the Moment Adjusted Imputation error model in the spectral count refinement as a post PLGEM-STN for improving sensitivity for quantitation of low-abundance proteins by reducing spectral count variability. The statistical framework, automated spectral count refinement by integrating the two statistical tools, was tested with LC-MS/MS datasets of MDA-MB468 breast cancer cells grown under normal and glucose deprivation conditions. We identified about 30% more quantifiable proteins that were found to be low-abundance proteins, which were initially filtered out by the PLGEM-STN analysis. This newly developed statistical framework provides a reliable abundance measurement of low-abundance proteins in the spectral count-based label-free proteome quantification and enabled us to detect low-abundance proteins that could be functionally important in cellular processes.

Early defects in translation elongation factor 1α levels at excitatory synapses in α-synucleinopathy.

Cognitive decline and dementia in neurodegenerative diseases are associated with synapse dysfunction and loss, which may precede neuron loss by several years. While misfolded and aggregated α-synuclein is recognized in the disease progression of synucleinopathies, the nature of glutamatergic synapse dysfunction and loss remains incompletely understood. Using fluorescence-activated synaptosome sorting (FASS), we enriched excitatory glutamatergic synaptosomes from mice overexpressing human alpha-synuclein (h-αS) and wild-type littermates to unprecedented purity. Subsequent label-free proteomic quantification revealed a set of proteins differentially expressed upon human alpha-synuclein overexpression. These include overrepresented proteins involved in the synaptic vesicle cycle, ER-Golgi trafficking, metabolism and cytoskeleton. Unexpectedly, we found and validated a steep reduction of eukaryotic translation elongation factor 1 alpha (eEF1A1) levels in excitatory synapses at early stages of h-αS mouse model pathology. While eEF1A1 reduction correlated with the loss of postsynapses, its immunoreactivity was found on both sides of excitatory synapses. Moreover, we observed a reduction in eEF1A1 immunoreactivity in the cingulate gyrus neuropil of patients with Lewy body disease along with a reduction in PSD95 levels. Altogether, our results suggest a link between structural impairments underlying cognitive decline in neurodegenerative disorders and local synaptic defects. eEF1A1 may therefore represent a limiting factor to synapse maintenance.

Simultaneous Improvement in the Precision, Accuracy, and Robustness of Label-free Proteome Quantification by Optimizing Data Manipulation Chains.

The label-free proteome quantification (LFQ) is multistep workflow collectively defined by quantification tools and subsequent data manipulation methods that has been extensively applied in current biomedical, agricultural, and environmental studies. Despite recent advances, in-depth and high-quality quantification remains extremely challenging and requires the optimization of LFQs by comparatively evaluating their performance. However, the evaluation results using different criteria (precision, accuracy, and robustness) vary greatly, and the huge number of potential LFQs becomes one of the bottlenecks in comprehensively optimizing proteome quantification. In this study, a novel strategy, enabling the discovery of the LFQs of simultaneously enhanced performance from thousands of workflows (integrating 18 quantification tools with 3,128 manipulation chains), was therefore proposed. First, the feasibility of achieving simultaneous improvement in the precision, accuracy, and robustness of LFQ was systematically assessed by collectively optimizing its multistep manipulation chains. Second, based on a variety of benchmark datasets acquired by various quantification measurements of different modes of acquisition, this novel strategy successfully identified a number of manipulation chains that simultaneously improved the performance across multiple criteria. Finally, to further enhance proteome quantification and discover the LFQs of optimal performance, an online tool (https://idrblab.org/anpela/) enabling collective performance assessment (from multiple perspectives) of the entire LFQ workflow was developed. This study confirmed the feasibility of achieving simultaneous improvement in precision, accuracy, and robustness. The novel strategy proposed and validated in this study together with the online tool might provide useful guidance for the research field requiring the mass-spectrometry-based LFQ technique.

Regional Differences of the Urinary Proteomes in Healthy Chinese Individuals.

Objective Urine is a promising biomarker source for clinical proteomics studies. Regional physiological differences are common in multi-center clinical studies. In this study, we investigate whether significant differences are present in the urinary proteomes of individuals from different regions in China. Methods In this study, morning urine samples were collected from healthy urban residents in three regions of China (Haikou, Xi'an and Xining) and urinary proteins were preserved using a membrane-based method (Urimem). The urine proteomes of 27 normal samples were analyzed using LC-MS/MS and compared among three regions. Functional annotation of the differential proteins among the three areas was analyzed using the DAVID online database, and pathway enrichment of the differential urinary proteins was analyzed using KEGG. Results We identified 1898 proteins from Urimem samples using label-free proteome quantification, of which 56 urine proteins were differentially expressed among the three regions (P < 0.05). Hierarchical clustering analysis showed that inter-regional differences caused less significant changes in the urine proteome than inter-sex differences. After gender stratification, 16 differential proteins were identified in male samples and 84 differential proteins were identified in female samples. Among these differential proteins, several proteins have been previously reported as urinary disease biomarkers. Conclusions Urimem will facilitate urinary protein storage for large-scale urine sample collection. Regional differences are a confounding factor influencing the urine proteome and should be considered in future multi-center biomarker studies.

Proteomics of acquired pellicle in gastroesophageal reflux disease patients with or without erosive tooth wear

ObjectivesThis in vivo study compared the protein profile of the acquired enamel pellicle (AEP) in volunteers 1) with gastroesophageal reflux disease (GERD) and erosive tooth wear (ETW) (BEWE ≥ 9; GE group); 2) with GERD without ETW (BEWE = 0; GNE group) and 3) control (without GERD and BEWE = 0; C group). Materials and methodsTwenty-four subjects (8/group) participated. AEP was formed during 120 min and collected. After protein extraction, the samples were submitted to reverse phase liquid chromatography coupled to mass spectrometry. Label-free proteomic quantification was performed using Protein Lynx Global Service software. ResultsIn total, 458 proteins were identified. Seventy-six proteins were common to all the groups. The proteomic profile of the AEP was quite different among the distinct groups. The numbers of proteins exclusively found in the C, GE and GNE groups were 113, 110 and 81, respectively. Most of the proteins exclusively identified in the C and GNE groups bind metals, while those in the GE group are mainly membrane proteins. Many proteins were found exclusively in the reflux groups. In the quantitative analyses, when the GNE group was compared with the GE group, the proteins with the highest decreases were Lysozyme C, Antileukoproteinase, Cathepsin G, Neutrophil defensins and Basic salivary proline-rich proteins, while those with the highest increases were subunits of Hemoglobin, Albumin and isoforms of Cystatin. ConclusionProfound alterations in the proteomic profile of the AEP were seen in GNE compared with GE volunteers, which might play a role in the resistance to ETW seen in the first. Clinical significanceThis pioneer study compared the proteomic profile of the AEP of patients with GERD with or without ETW. Increased proteins in those without ETW might be protective and are good candidates to be added to dental products to protect against erosion caused by intrinsic acids.

Untargeted analysis of the airway proteomes of children with respiratory infections using mass spectrometry based proteomics

The upper airway – which consists mainly of the naso- and oro-pharynx - is the first point of contact between the respiratory system and microbial organisms that are ubiquitous in the environment. It has evolved highly specialised functions to address these constant threats whilst facilitating seamless respiratory exchange with the lower respiratory tract. Dysregulation of its critical homeostatic and defence functions can lead to ingress of pathogens into the lower respiratory tract, potentially leading to serious illness. Systems-wide proteomic tools may facilitate a better understanding of mechanisms in the upper airways in health and disease. In this study, we aimed to develop a mass spectrometry based proteomics method for characterizing the upper airways proteome. Naso- and oropharyngeal swab samples used in all our experiments had been eluted in the Universal Transport Media (UTM) containing significantly high levels of bovine serum albumin. Our proteomic experiments tested the optimal approach to characterize airway proteome on swab samples eluted in UTM based on the number of proteins identified without BSA depletion (Total proteome: Protocol A) and with its depletion using a commercial kit; Allprep, Qiagen (cellular proteome: Protocol B, Ci, and Cii). Observations and lessons drawn from protocol A, fed into the design and implementation of protocol B, and from B to protocol Ci and finally Cii. Label free proteome quantification was used in Protocol A (n = 6) and B (n = 4) while commercial TMT 10plex reagents were used for protocols Ci and ii (n = 83). Protocols Ci and ii were carried out under similar conditions except for the elution gradient: 3 h and 6 h respectively. Swab samples tested in this study were from infants and children with and without upper respiratory tract infections from Kilifi County Hospital on the Kenyan Coast. Protocol A had the least number of proteins identified (215) while B produced the highest number of protein identifications (2396). When Protocol B was modified through sample multiplexing with TMT to enable higher throughput (Protocol Ci), the number of protein identified reduced to 1432. Modification of protocol Ci by increasing the peptide elution time generated Protocol Cii that substantially increased the number of proteins identified to 1875. The coefficient of variation among the TMT runs in Protocol Cii was <20%. There was substantial overlap in the identity of proteins using the four protocols. Our method was were able to identify marker proteins characteristically expressed in the upper airway. We found high expression levels of signature nasopharyngeal and oral proteins, including BPIFA1/2 and AMY1A, as well as a high abundance of proteins related to innate and adaptive immune function in the upper airway. We have developed a sensitive systems-level proteomic assay for the systematic quantification of naso-oro-pharyngeal proteins. The assay will advance mechanistic studies of respiratory pathology, by providing an untargeted and hypothesis-free approach of examining the airway proteome.

Discovery of the Consistently Well-Performed Analysis Chain for SWATH-MS Based Pharmacoproteomic Quantification.

Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) has emerged as one of the most popular techniques for label-free proteome quantification in current pharmacoproteomic research. It provides more comprehensive detection and more accurate quantitation of proteins comparing with the traditional techniques. The performance of SWATH-MS is highly susceptible to the selection of processing method. Till now, ≥27 methods (transformation, normalization, and missing-value imputation) are sequentially applied to construct numerous analysis chains for SWATH-MS, but it is still not clear which analysis chain gives the optimal quantification performance. Herein, the performances of 560 analysis chains for quantifying pharmacoproteomic data were comprehensively assessed. Firstly, the most complete set of the publicly available SWATH-MS based pharmacoproteomic data were collected by comprehensive literature review. Secondly, substantial variations among the performances of various analysis chains were observed, and the consistently well-performed analysis chains (CWPACs) across various datasets were for the first time generalized. Finally, the log and power transformations sequentially followed by the total ion current normalization were discovered as one of the best performed analysis chains for the quantification of SWATH-MS based pharmacoproteomic data. In sum, the CWPACs identified here provided important guidance to the quantification of proteomic data and could therefore facilitate the cutting-edge research in any pharmacoproteomic studies requiring SWATH-MS technique.