Glycation plays a pathogenic role in many age-related degenerative pathological conditions, such as diabetes, end-stage renal diseases, and cardiovascular diseases. Mass spectrometry-based qualitative and quantitative analysis methods have been greatly developed and contribute to our understanding of protein glycation. However, it is still challenging to sensitively and accurately quantify endogenous glycated proteome in biological samples. Herein, we proposed an integrated and robust quantitative strategy for comprehensive profiling of early-stage glycated proteome. In this strategy, a filter-assisted sample preparation method was applied to reduce sample loss and improve reproducibility of sample preparation, contributing to high-throughput analysis and accurate quantification of endogenous glycated proteins with low abundance. Standard glycated peptides were spiked and performed the subsequent process together with complex samples both in label-free quantification and multiple reaction monitoring (MRM) analysis, contributing to the improvement of quantitative accuracy. In parallel, a novel approach was developed for the synthesis of heavy isotope-labeled glycated peptides used in MRM analysis. By this way, a total of 1128 endogenous glycated peptides corresponding to 203 serum proteins were identified from 60 runs of 10 pairs of hemodialysis patients with and without cardiovascular complications, and 234 glycated peptides corresponding to 63 proteins existed in >70% runs, among which 17 peptides were discovered to be differentially glycated (P < 0.05, fold-change > 1.5 or

Data dependent acquisition (DDA) is the method of choice for mass spectrometry based proteomics discovery experiments, data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirement to perform a DIA analysis is the availability of spectral libraries for the peptide identification and quantification. Several researches were already conducted regarding the creation of spectral libraries from DDA analyses and obtaining identifications with these in DIA measurements. But so far only few experiments were conducted, to estimate the effect of these libraries on the quantitative level. In this work we created a spike-in gold standard dataset with known contents and ratios of proteins in a complex sample matrix. With this dataset, we first created spectral libraries using different sample preparation approaches with and without sample prefractionation on peptide and protein level. Two different search engines were used for protein identification. In total, five different spike-in states were compared with DIA analyses, comparing eight different spectral libraries generated by varying approaches and one library free method, as well as one default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding analyses was inspected, but also the number of expected and identified significant quantifications and their ratios were thoroughly examined. We found, that while libraries of prefractionationed samples are generally larger, the actually yielded identifications are not increased compared to repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantifications is also highly dependent on the applied spectra library and also whether the peptide or protein level is analysed. Overall, the reproducibility and accuracy of DIA is superior to DDA in all analysed approaches.

Label-free quantification (LFQ) and isobaric labeling quantification (ILQ) are among the most popular protein quantification workflows in discovery proteomics. Here, we compared the TMT SPS/MS3 10-plex workflow to a label free single shot data-independent acquisition (DIA) workflow on a controlled sample set. The sample set consisted of ten samples derived from 10 biological replicates of mouse cerebelli spiked with the UPS2 protein standard in five different concentrations. For a fair comparison, we matched the instrument time for the two workflows. The LC–MS data were acquired at two facilities to assess interlaboratory reproducibility. Both methods resulted in a high proteome coverage (>5000 proteins) with low missing values on protein level (

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years due to the technical improvement of mass spectrometers, and now allow to extensively characterize complex protein mixtures. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, which appear as an attractive way to analyze differential protein expression in complex biological samples. Classical label-free quantitative workflows are based either on spectral counting of MS/MS sequencing scans for each protein, or on the extraction of peptide ion peak area values in the LC-MS map composed of all the survey MS scans acquired during the chromatographic gradient. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we provide a dual proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate, that was used to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). This dataset can also be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods

Using our strongly immunogenic SmT1 SARS-CoV-2 spike antigen platform, we developed novel antigens based on the Beta & Delta variants of concern. These antigens elicited higher neutralizing antibody activity to the corresponding variant than comparable vaccine formulations based on the original reference strain, while a multivalent vaccine generated cross-neutralizing activity to all three variants. This suggests that while current vaccines may be effective at reducing severe disease to existing variants of concern, variant-specific antigens, whether in a mono- or multivalent vaccine, may be required to induce optimal immune responses and reduce infection against arising variants. Methods Antigens SmT1v3-R, -B and –D constructs are based on SARS-CoV-2 spike trimers described previously22,23 but with C-terminal FLAG/His affinity tags removed. Briefly, the SARS-CoV-2 reference strain spike ectodomain sequence (amino acids 1-1208 derived from Genbank accession number MN908947) was codon-optimized for Chinese Hamster Ovary (CHO) cells and synthesized by GenScript. Within the construct, the spike glycoprotein was preceded by its natural N-terminal signal peptide and fused at the C-terminus to human resistin (accession number NP_001180303.1, amino acids 23-108). Mutations were added to stabilize the generated spike protein as previously described; amino acids 682-685 (RRAR) and 986-987 (KV) were replaced with GGAS and PP, respectively24,25. Constructs were then cloned into the pTT241 plasmid. Expression constructs for VOC spike variants were prepared by re-synthesizing and replacing restriction fragments encompassing mutations present in the Beta (SmT1v3-B) (D80A, D215G, 241del, 242del, 243del, K417N, E484K, N501Y, D614G, A701V) and Delta (SmT1v3-D) (T19R, G142D, E156-, F157-, R158G, L452R, T478K, D614G, P681R, D950N) variants, while maintaining the codon-optimized sequences of the remaining amino acids used for SmT1v3-R expression. Stably transfected pools were established by MSX selection using the CHO2353™ cell line and used for 10-day fed-batch productions with cumate induction as described23. Spike proteins were purified using a proprietary multi-step non-affinity-based process and formulated in Dulbecco’s Phosphate Buffered Saline (DPBS; Hyclone, Logan, Utah, USA) adjusted to pH 7.8 at protein concentrations of 1.1-1.4 mg/ml. Purified proteins analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and analytical size-exclusion ultra-high performance liquid chromatography (SEC-UPLC). SEC-UPLC was run on an Acquity H-Class Bio UPLC system (Wyatt Technology, Santa Barbara, CA, USA) in phosphate-buffered saline (PBS) + 0.02% Tween-20 on a 4.6 × 300 mm Acquity BEH450 column (2.5 μm bead size; Waters Limited, Mississauga, ON, Canada) coupled to a miniDAWN Multi-Angle Light Scattering (MALS) detector and Optilab T-rEX refractometer (Wyatt). The identity and purity of the antigens was also confirmed by mass spectrometry. Absence of endotoxin contamination was verified using Endosafe cartridge-based Limulus amebocyte lysate tests (Charles River Laboratories, Charleston, SC, USA). Immunization & sample collection Female C57BL/6 mice (6-8 weeks old) were obtained from Charles River Laboratories (Saint-Constant, Canada). Animals were maintained at the small animal facility of the National Research Council Canada (NRC) in accordance with the guidelines of the Canadian Council on Animal Care. All procedures performed on animals in this study were approved by our Institutional Review Board (NRC Human Health Therapeutics Animal Care Committee) and covered under animal use protocol 2020.10. All experiments were carried out in accordance with the ARRIVE guidelines. Mouse experiments (n=10 per group) consisted of 2 separate equal-sized cohorts, where animals were treated identically but had procedures conducted on different days. Data from both cohorts was combined and included for analysis. Seven out of a total of 70 mice receiving AddaS03-adjuvanted formulations had to be excluded due to high local reactogenicity at the site of injection. As such, the AddaS03 groups had 9-10 mice per group included in the final analysis, except for one group (1 µg SmT1v3-R) where results from 7 mice were included. Antigen and adjuvant vaccine components were admixed and diluted in phosphate-buffered saline (PBS; Thermo Fisher Scientific, Waltham, MA, USA) prior to administration in a final volume of 50 µL per dose. Sulfated lactosyl archaeol (SLA) archaeosomes are proprietary NRC adjuvants that were prepared as previously described26. Levels of endotoxin in the SLA archaeosomes were verified by the Endosafe® cartridge-based Limulus amebocyte lysate test (Charles River Laboratories) and confirmed to be <0.1 EU per mg. AddaS03 (Invivogen, San Diego, CA, USA) was prepared as per manufacturer’s instructions. Animals were immunized by intramuscular (i.m.) injection (50 µL) into the left tibialis anterior (T.A.) muscle on Days 0 and 21 with various vaccine formulations as described above. On Day 28, mice were anesthetized with isoflurane and then euthanized by cervical dislocation prior to collection of spleens for measurement of cellular immune responses by IFN-γ ELISpot. Mice were bled via the submandibular vein on Days 20 and 28 with recovered serum used for quantification of antigen-specific IgG antibody levels and neutralization assays. Samples were simultaneously collected from 10 naïve animals for the assessment of background immune responses. Each of the samples from the individual mice was tested separately in the various readouts. Anti-Spike IgG ELISA Anti-spike total IgG titers in serum were measured by indirect ELISA with SmT1-R, -B or -D as previously described10. Briefly, 96–well high-binding ELISA plates (Thermo Fisher Scientific) were coated with 0.3 µg/mL SmT1 protein diluted in PBS. Serum samples were serially diluted 3.162-fold and added to the plates to allow for binding of antibodies to the protein. Bound IgG was detected with goat anti-mouse IgG -HRP (1:4,000, Southern Biotech, Birmingham, AL, USA) prior to the addition of the substrate o-phenylenediamine dihydrochloride (OPD, Sigma-Aldrich). Bound IgG Abs were detected spectrophotometrically at 450 nm. Titers for IgG in serum were defined as the dilution that resulted in an absorbance value (OD450) of 0.2 and were calculated using XLfit software (ID Business Solutions, Guildford, UK). Samples that did not reach the target OD were assigned the value of the lowest tested dilution (i.e. 100) for analysis purposes. No detectable titers were measured in serum samples from naïve control animals. IFN- γ ELISpot IFN- γ ELISpot was also conducted as previously described10. The levels of spike glycoprotein-specific T cells were quantified by ELISpot using a mouse IFN-γ kit (Mabtech Inc., Cincinnati, OH, USA). A spike peptide library (JPT Peptide Technologies GmbH) based on the reference strain sequence and consisting of 315 peptides (15mers overlapping by 11 amino acids with the last peptide consisting of a 17mer) was used to stimulate splenocytes isolated from each of the mice. The library was split into 3 subpools and used to separately stimulate 4x105 cells in duplicate at a final concentration of 2 µg/mL per peptide. Cells were also incubated without any stimulants to measure background responses. Spots were counted using an automated ELISpot plate reader (Cellular Technology LTD, Beachwood, OH, USA). For each animal, values obtained with media alone were subtracted from those obtained with each of the spike peptide pools and then combined to yield an overall number of antigen-specific IFN-γ+ SFC/106 splenocytes per animal.
Cell-based SARS CoV-2 Spike-ACE2 Binding Assay The ability serum to neutralize the binding of labeled SARS-CoV-2 spike trimers (SmT1) to Vero E6 cells was measured as previously described10. Indicated dilutions of mouse serum were mixed with 250 ng of biotinylated spike and 1x105 Vero E6 cells (ATCC® CRL-1586™). The amount of bound spike was quantified using a Streptavidin-phycoerythrin conjugate prior to acquisition on an LSR Fortessa (Becton Dickinson). For analysis purposes, samples with calculated values ≤ 0 were assigned a value of 0. The levels of neutralization were normalized to the World Health Organization human standard reference material (20/136 from NIBSC, South Mimms, UK) to obtain the anti-SARS-CoV-2 activity (IU/mL) in undiluted mouse serum. Pseudovirus Neutralization Assay Pseudovirus neutralization assay was performed in 384-well plate format adapted from previously described protocol and modification27,28. Briefly, 4-fold serial dilutions of the serum samples were incubated with diluted virus at a 2:1 ratio for 1 hour at 37°C before addition to HEK293-ACE2/TMPRSS2 cells obtained from BEI Resources repository of ATCC and the NIH (NR-55293). Infectivity was then measured by luminescence readout per well. Bright-Glo luciferase reagent (Promega, E2620) was added to wells for 2 min before reading with a PerkinElmer Envision instrument. Neutralization Titer 50 (NT50) were calculated with nonlinear regression (log[inhibitor] versus normalized response – variable slope) with the 100% and 0% constraint. Pseudotyped lentiviral particles were produced expressing the SARS-CoV-2 variant spikes under CMV promotor and were packaged onto lentiviral vectors obtained through BEI Resources, NIAID, NIH: SARS-Related Coronavirus 2, Wuhan-Hu-1 (GenBank # NC_045512) Spike-Pseudotyped Lentiviral Kit, NR-52948. pcDNA3.3-SARS2-B.1.617.2 expressing the SARS-CoV-2 B.1.617.2 (Delta variant) (Addgene plasmid # 172320) and pcDNA3.3_CoV2_501V2 expressing SARS-CoV-2, B.1.351 (Beta variant) (Addgene plasmid # 170449) spike proteins were gifts from David Nemazee. Statistical analysis Data were analyzed using GraphPad Prism® version 8 (GraphPad Software). Statistical significance of the difference

The human serum proteome has been extensively screened for biomarkers. However, the large dynamic range of protein concentrations in serum and the presence of highly abundant and large molecular weight proteins, make identification and detection changes in the amount of low-molecular weight proteins (LMW, molecular weight ? 30kDa) difficult. Here, we developed a gel-filter method including four layers of different concentration of tricine SDS-PAGE-based gels to block high-molecular weight proteins and enrich LMW proteins. By utilizing this method, we identified 1,576 proteins (n = 2) from 10 ?L serum. Among them, 559 (n = 2) proteins belonged to LMW proteins. Furthermore, this gel-filter method could identify 67.4% and 39.8% more LMW proteins than that in representative methods of glycine SDS-PAGE and optimized-DS, respectively. By utilizing SILAC-AQUA approach with labeled recombinant protein as internal standard, the recovery rate for GST spiked in serum during the treatment of gel-filter, optimized-DS, and ProteoMiner was 33.1 ± 0.01%, 18.7 ± 0.01% and 9.6 ± 0.03%, respectively. These results demonstrate that the gel-filter method offers a rapid, highly reproducible and efficient approach for screening biomarkers from serum through proteomic analyses.

7922 compounds were downloaded from NPC database (https://tripod.nih.gov/npc/). In order to eliminate the non-specific binders, some criteria including molecular weight, between 100 to 1000 g/mol; number of rotatable bonds, <100; number of atoms, between 10 and 100; number of aliphatic and aromatic rings, <10; number of hydrogen-bond acceptor and donors, <10 were set and as a result the total number of compounds was decreased to 6654. These ligands were prepared using LigPrep module of Maestro at neutral pH (LigPrep, Schrodinger v.2017). In molecular docking, we used following protein structure: Spike Protein/ACE-2, (PDB, 6M0J). The protein was prepared using Protein Preparation module of Maestro. PROPKA was used for determination of protonation states of amino acid residues. Restrained minimization was performed with OPLS3 force field for the protein using 0.3 Å heavy atom convergence. Docking was performed with Glide/SP using default settings. Top-100 docking poses were provided.

A rapid detection method for SARS-CoV-2 spike protein is essential for control of COVID19. We investigated various combinations of engineered nanobodies in a sandwich ELISA to detect the Spike protein of SARS-CoV-2. We have identified an optimal combination of nanobodies. These were selectively functionalised to further improve antigen capture. This dataset contains data from ELISA experiments described in the manuscript.

Plate coating of nanobodies for ELISA by passive adsorption vs biotinylation was compared. A series of nanobody pairings (two cluster 2 ACE2-binding epitope and two cluster 1 CR3022 epitope) were screened for optimum sensitivity. The optimal pair were then tested against a series of SARS-COV-2 antigens: recombinant spike 1 protein; recombinant receceptor binding domain (RBD); pseudotyped HIV-1 and heat-empigen inactivated SARS-CoV-2 virus. X-ray irradiated SARS-CoV-2 was also tested. Sensitivity to these antigens was compared with nanobodies biotinylated a) site-selectively and b) in a non-specific stochastic manner. Batch-to-batch viral variation and effects of inactivating agents were investigated. Limit of detection was compared against delta and beta viral mutants. Combining optimal nanobody pairing and site-selective biotinylation, we observed a limit of detection of 147 pg/mL for Spike protein; 33 pg/mL for RBD; 16 TCID50/mL of pseudovirus and 15 ffu/mL of heat-Empigen inactivated SARS-CoV-2. The pairing also showed sensitivity towards delta variant. We have demonstrated the use and sensitivity of nanobodies in ELISA by detection of recombinant and viral SARS-CoV-2 antigens.

Methods The data supplied is raw absorbance data for ELISA. The data was collected on a Spectramax M3 microplate reader (Molecular Devices). The data was processed using Prism software. Variable slopes were modelled using Prism's sigmoidal 4-parameter logistic curve. To determine slope gradient, values in linear range were modelled using simple linear regression. Standard deviation was calculated using the built-in prism analysis.

For modeling approaches in systems biology, knowledge of the absolute abundances of cellular proteins is essential. One way to gain this knowledge is the use of quantification concatamers (QconCATs), which are synthetic proteins consisting of proteotypic peptides derived from the target proteins to be quantified. The QconCAT protein is labeled with a heavy isotope upon expression in E. coli and known amounts of the purified protein are spiked into a whole cell protein extract. Upon tryptic digestion, labeled and unlabeled peptides are released from the QconCAT protein and the native proteins, respectively, and both are quantified by LC-MS/MS. The labeled Q-peptides then serve as standards for determining the absolute quantity of the native peptides/proteins. Here, we have applied the QconCAT approach to Chlamydomonas reinhardtii for the absolute quantification of the major proteins and protein complexes driving photosynthetic light reactions in the thylakoid membranes and carbon fixation in the pyrenoid. We found that with 25.2 attomol/cell the Rubisco large subunit makes up 6.6% of all proteins in a Chlamydomonas cell and with this exceeds the amount of the small subunit by a factor of 1.56. EPYC1, which links Rubisco to form the pyrenoid, is eight times less abundant than RBCS, and Rubisco activase is 32-times less abundant than RBCS. With 5.2 attomol/cell, photosystem II is the most abundant complex involved in the photosynthetic light reactions, followed by plastocyanin, photosystem I and the cytochrome b6/f complex, which range between 2.9 and 3.5 attomol/cell. The least abundant complex is the ATP synthase with 2 attomol/cell. While applying the QconCAT approach, we have been able to identify many potential pitfalls associated with this technique. We analyze and discuss these pitfalls in detail and provide an optimized workflow for future applications of this technique.

With fast growth, synthetic biology powers us with the capability to produce high commercial value products in an efficient resource/energy-consuming manner. Comprehensive knowledge of the protein regulatory network of a bacterial host chassis, e.g., the actual amount of the given proteins, is the key to building cell factories for certain target hyperproduction. Many talent methods have been introduced for absolute quantitative proteomics. However, for most cases, a set of reference peptides with isotopic labeling (e.g., SIL, AQUA, QconCAT) or a set of reference proteins (e.g., commercial UPS2 kit) needs to be prepared. The higher cost hinders these methods for large sample research. In this work, we proposed a novel metabolic labeling-based absolute quantification approach (termed nMAQ). The reference Corynebacterium glutamicum strain is metabolically labeled with 15N, and a set of endogenous anchor proteins of the reference proteome is quantified by chemically synthesized light (14N) peptides. The prequantified reference proteome was then utilized as an internal standard (IS) and spiked into the target (14N) samples. SWATH-MS analysis is performed to obtain the absolute expression levels of the proteins from the target cells. The cost for nMAQ is estimated to be less than 10 dollars per sample. We have benchmarked the quantitative performance of the novel method. We believe this method will help with the deep understanding of the intrinsic regulatory mechanism of C. glutamicum during bioengineering and will promote the process of building cell factories for synthetic biology.

Abbreviations: SD =  standard deviation.

a: concentrations in the spiked samples were calculated after subtracting the mean levels (n = 3) measured in the non-spiked pooled urine samples during each validation batch.

The human serum proteome has been extensively screened for biomarkers. However, the large dynamic range of protein concentrations in serum and the presence of highly abundant and large molecular weight proteins, make identification and detection changes in the amount of low-molecular weight proteins (LMW, molecular weight ≤ 30kDa) difficult. Here, we developed a gel-filter method including four layers of different concentration of tricine SDS-PAGE-based gels to block high-molecular weight proteins and enrich LMW proteins. By utilizing this method, we identified 1,576 proteins (n = 2) from 10 μL serum. Among them, 559 (n = 2) proteins belonged to LMW proteins. Furthermore, this gel-filter method could identify 67.4% and 39.8% more LMW proteins than that in representative methods of glycine SDS-PAGE and optimized-DS, respectively. By utilizing SILAC-AQUA approach with labeled recombinant protein as internal standard, the recovery rate for GST spiked in serum during the treatment of gel-filter, optimized-DS, and ProteoMiner was 33.1 ± 0.01%, 18.7 ± 0.01% and 9.6 ± 0.03%, respectively. These results demonstrate that the gel-filter method offers a rapid, highly reproducible and efficient approach for screening biomarkers from serum through proteomic analyses.

Numerous reverse transcription polymerase chain reaction (RT-PCR) tests have emerged over the past year as the gold standard for detecting millions of cases of SARS-CoV-2 reported daily worldwide. However, problems with critical shortages of key reagents such as PCR primers and RNA extraction kits and unpredictable test reliability related to high viral replication cycles have triggered the need for alternative methodologies to PCR to detect specific COVID-19 proteins. Several authors have developed methods based on liquid chromatography with tandem mass spectrometry (LC–MS/MS) to confirm the potential of the technique to detect two major proteins, the spike and the nucleoprotein, of COVID-19. In the present work, an S-Trap mini spin column digestion protocol was used for sample preparation prodromal to LC–MS/MS analysis in multiple reactions monitoring ion mode (MRM) to obtain a comprehensive method capable of detecting different viral proteins. The developed method was applied to n. 81 oro/nasopharyngeal swabs submitted in parallel to quantitative reverse transcription PCR (RT-qPCR) assays to detect RdRP, the S and N genes specific for COVID-19, and the E gene for all Sarbecoviruses, including SARS-CoV-2 (with cycle negativity threshold set to 40). A total of 23 peptides representative of the six specific viral proteins were detected in the monitoring of 128 transitions found to have good ionic currents extracted in clinical samples that reacted differently to the PCR assay. The best instrumental response came from the FLPFQFGR sequence of spike [558−566] peptide used to test the analytical performance of the method that has good sensitivity with a low false-negative rate. Transition monitoring using a targeted MS approach has the great potential to detect the fragmentation reactions of any peptide molecularly defined by a specific amino acid sequence, offering the extensibility of the approach to any viral sequence including derived variants and thus providing insights into the development of new types of clinical diagnostics.

Recovery study results of PR3. Negative urine samples were spiked with low, medium and high concentration of standard.

The standard approach for proteomic data acquisition of isobaric-tagged samples by mass spectrometry is data-dependent acquisition. This semistochastic, identification-first paradigm generates a wealth of peptide-level data without regard to relative abundance. We introduce a data acquisition concept called sequential windowed acquisition of reporter masses (SWARM). This approach performs quantitation first, thereby allowing subsequent acquisition decisions to be predicated on user-defined patterns of reporter ion intensities. The efficacy of this approach is validated through experiments with both synthetic mixtures of Escherichia coli ribosomes spiked into human cell lysates at known ratios and the quantitative evaluation of the human proteome’s response to the inhibition of cullin-based protein ubiquitination via the small molecule MLN4924. We find that SWARM-informed parallel reaction monitoring acquisitions display effective acquisition biasing toward analytes displaying quantitative characteristics of interest, resulting in an improvement in the detection of differentially abundant analytes. The SWARM concept provides a flexible platform for the further development of new acquisition methods.

Label-free proteomics expression data sets often exhibit data heterogeneity and missing values, necessitating the development of effective normalization and imputation methods. The selection of appropriate normalization and imputation methods is inherently data-specific, and choosing the optimal approach from the available options is critical for ensuring robust downstream analysis. This study aimed to identify the most suitable combination of these methods for quality control and accurate identification of differentially expressed proteins. In this study, we developed nine combinations by integrating three normalization methods, locally weighted linear regression (LOESS), variance stabilization normalization (VSN), and robust linear regression (RLR) with three imputation methods: k-nearest neighbors (k-NN), local least-squares (LLS), and singular value decomposition (SVD). We utilized statistical measures, including the pooled coefficient of variation (PCV), pooled estimate of variance (PEV), and pooled median absolute deviation (PMAD), to assess intragroup and intergroup variation. The combinations yielding the lowest values corresponding to each statistical measure were chosen as the data set’s suitable normalization and imputation methods. The performance of this approach was tested using two spiked-in standard label-free proteomics benchmark data sets. The identified combinations returned a low NRMSE and showed better performance in identifying spiked-in proteins. The developed approach can be accessed through the R package named ’lfproQC’ and a user-friendly Shiny web application (https://dabiniasri.shinyapps.io/lfproQC and http://omics.icar.gov.in/lfproQC), making it a valuable resource for researchers looking to apply this method to their data sets.

Diagnostic classification accuracy is critical in expression proteomics to ensure that as many true differences as possible are identified with acceptable false-positive rates. We present a comparison of the diagnostic accuracy of iTRAQ with three label-free methods, peak area, spectral counting, and emPAI, for relative quantification using a spiked proteome standard. We provide the first validation of emPAI for intersample relative quantification and find clear differences among the four quantification approaches that could be considered when designing an experiment. Spectral counting was observed to perform surprisingly well in all regards. Peak area performed best for smaller fold differences and was shown to be capable of discerning a 1.1-fold difference with acceptable specificity and sensitivity. The performance of iTRAQ was dramatically worse than the label-free methods with low abundance proteins. Using the iTRAQ data set for validation, we also demonstrate a novel iTRAQ analysis regime that avoids the use of ratios in significance testing and outperforms a common commercial alternative.

The type VI secretion system (T6SS) is a contractile injection apparatus that translocates a spike loaded with various effectors directly into eukaryotic and prokaryotic target cells. Such T6SS spike consists of a needle-shaped trimer of VgrG proteins topped by a conical and sharp PAAR protein that facilitates puncturing of the target membrane. T6SS-delivered effector proteins can be either fused to one of the two spike proteins or interact with either in a highly specific manner. In Agrobacterium tumefaciens the T6SS effector Tde1 is targeted to its cognate VgrG1 protein. Here, we attempted to use a VgrG shuttle to deliver a heterologous T6SS effector by directing Tde1 onto a T6SS spike in Pseudomonas aeruginosa. For this, we designed chimeras between VgrG1 from A. tumefaciens and VgrG1a from P. aeruginosa and showed that modification of the spike protein hampered T6SS functionality in the presence of the Tde1 effector complex. We provide evidence suggesting that Tde1 specifically binds to the VgrG spike in the heterologous environment and propose that there are additional requirements to allow proper effector delivery and translocation. Our work sheds light on complex aspects of the molecular mechanisms of T6SS delivery and highlights some limitations on how effectors can be translocated using this nanomachine.