In-depth evaluation of software tools for data-independent acquisition based label-free quantification

Multispecies Benchmark Analysis for LC-MS/MS Validation and Performance Evaluation in Bottom-Up Proteomics

We present an instrument-independent benchmark procedure and software (LFQ_bout) for the validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. The procedure enables a back-to-back comparison of common and emerging workflows, e.g., diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary and inadequately documented settings or black-box data processing algorithms. It enhances the overall performance and quantification accuracy by recognizing and reporting common quantification errors.

On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics

The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E. coli dataset demonstrating in a number of cases that erroneous data processing methods may lead to a low CV which has nothing to do with these methods' performances in quantitation.

Mix24X, a Lab-Assembled Reference to Evaluate Interpretation Procedures for Tandem Mass Spectrometry Proteotyping of Complex Samples

Correct identification of the microorganisms present in a complex sample is a crucial issue. Proteotyping based on tandem mass spectrometry can help establish an inventory of organisms present in a sample. Evaluation of bioinformatics strategies and tools for mining the recorded datasets is essential to establish confidence in the results obtained and to improve these pipelines in terms of sensitivity and accuracy. Here, we propose several tandem mass spectrometry datasets recorded on an artificial reference consortium comprising 24 bacterial species. This assemblage of environmental and pathogenic bacteria covers 20 different genera and 5 bacterial phyla. The dataset comprises difficult cases, such as the Shigella flexneri species, which is closely related to Escherichia coli, and several highly sequenced clades. Different acquisition strategies simulate real-life scenarios: from rapid survey sampling to exhaustive analysis. We provide access to individual proteomes of each bacterium separately to provide a rational basis for evaluating the assignment strategy of MS/MS spectra when recorded from complex mixtures. This resource should provide an interesting common reference for developers who wish to compare their proteotyping tools and for those interested in evaluating protein assignment when dealing with complex samples, such as microbiomes.

Challenges and opportunities for single cell computational proteomics

Single-cell proteomics is growing rapidly and has made several technological advancements. As most research has been focused on improving instrumentation and sample preparation methods, very little attention has been given to algorithms responsible for identifying and quantifying proteins. Given the inherent difference between bulk data and single-cell data, it's necessary to realize that current algorithms being employed on single-cell data were designed for bulk data, and have underlying assumptions that may not hold true for single-cell data. In order to develop and optimize algorithms for single-cell data, we need to characterize the differences between single-cell data and bulk data, and assess how current algorithms perform on single-cell data. Here, we present a review of algorithms responsible for identifying and quantifying peptides and proteins. We will give a review of how each type of algorithm works, assumptions it relies on, how it performs on single-cell data, and possible optimizations and solutions that could be used to address the differences in single-cell data.

Proteome alterations during clonal isolation of established human pancreatic cancer cell lines

Clonal isolation is an integral step of numerous workflows in genome editing and cell engineering. It comprises the isolation of a single progenitor cell from a defined cell line population with subsequent expansion to obtain a monoclonal cell population. This process is associated with transient loss of cell–cell contacts and absence of a multicellular microenvironment. Previous studies have revealed transcriptomic changes upon clonal isolation with cell line specific extent. Since transcriptome alterations are only partially reflected on the proteome level, we sought to investigate the impact of clonal isolation on the cellular proteome to a depth of > 6000 proteins in three established pancreatic cancer cell lines. We show that clonal isolation does have an impact on the cellular proteome, however, with cell line specific extent, affecting different biological processes, and also depending on the isolation method. We demonstrate a different impact of clonal isolation on mesenchymal- and epithelial-derived cell lines mainly affecting cell proliferation, metabolism, cell adhesion and cellular stress. The results bear relevance to the field of genomic editing and cell engineering and highlight the need to consider the impact of clonal isolation when interpreting data stemming from experiments that include this step.

Forensic Investigation of Remnant Data on USB Storage Devices Sold in New Zealand

The digital forensic tools used by law enforcement agencies for forensic investigations are mostly proprietary and commercially expensive; although open-source tools are used, the investigations conducted with such tools are not verified by reputable organisations, and hence, users are reluctant to practice such tools. To address this issue, we experimentally evaluate three open-source forensic tools based on various requirements recommended by the National Institute of Standards and Technology (NIST) framework for forensic investigation. The experimental setup consists of a forensic workstation, write-blocker, and purchased USB hard drives investigated via digital forensic imaging tools, i.e., DC3DD, DCFLDD, and Guymager. We create various test cases, which distribute USB hard drives in different groups and investigate the functional and optional requirements of NIST along with recovering and analysing remnant data. We evaluate these forensic tools by analysing the log information, following, anonymously (to ensure that data were not disclosed or misused during or after the investigations) collecting, examining, and classifying the remnant data restored from the USB hard drives. We observe that the percentage of hardware resources usage and the processing time of each tool are remarkably different, e.g., Guymager was the fastest tool and met all the functional requirements in each test case, but it utilised more CPU and memory resources than DC3DD, DCFLDD. We note that 88.23% of the USB hard drives contained sensitive personal or business information (e.g., personal photos, bank transactions, and contracts). Subsequently, the remnant data analysis shows that consumers in New Zealand are unaware of personal data security and the associated vulnerabilities of data leakages.

Unresolved stalled ribosome complexes restrict cell-cycle progression after genotoxic stress

During the translation surveillance mechanism known as ribosome-associated quality control, the ASC-1 complex (ASCC) disassembles ribosomes stalled on the mRNA. Here, we show that there are two distinct classes of stalled ribosome. Ribosomes stalled by translation elongation inhibitors or methylated mRNA are short lived in human cells because they are split by the ASCC. In contrast, although ultraviolet light and 4-nitroquinoline 1-oxide induce ribosome stalling by damaging mRNA, and the ASCC is recruited to these stalled ribosomes, we found that they are refractory to the ASCC. Consequently, unresolved UV- and 4NQO-stalled ribosomes persist in human cells. We show that ribosome stalling activates cell-cycle arrest, partly through ZAK-p38MAPK signaling, and that this cell-cycle delay is prolonged when the ASCC cannot resolve stalled ribosomes. Thus, we propose that the sensitivity of stalled ribosomes to the ASCC influences the kinetics of stall resolution, which in turn controls the adaptive stress response.

Yeast Secretes High Amounts of Human Calreticulin without Cellular Stress

The ER chaperone calreticulin (CALR) also has extracellular functions and can exit the mammalian cell in response to various factors, although the mechanism by which this takes place is unknown. The yeast Saccharomyces cerevisiae efficiently secretes human CALR, and the analysis of this process in yeast could help to clarify how it gets out of eukaryotic cells. We have achieved a secretion titer of about 140 mg/L CALR in our S. cerevisiae system. Here, we present a comparative quantitative whole proteome study in CALR-secreting yeast using non-equilibrium pH gradient electrophoresis (NEPHGE)-based two-dimensional gel electrophoresis (2DE) as well as liquid chromatography mass spectrometry in data-independent analysis mode (LC-MSE). A reconstructed carrier ampholyte (CA) composition of NEPHGE-based first-dimension separation for 2DE could be used instead of formerly commercially available gels. Using LC-MSE, we identified 1574 proteins, 20 of which exhibited differential expression. The largest group of differentially expressed proteins were structural ribosomal proteins involved in translation. Interestingly, we did not find any signs of cellular stress which is usually observed in recombinant protein-producing yeast, and we did not identify any secretory pathway proteins that exhibited changes in expression. Taken together, high-level secretion of human recombinant CALR protein in S. cerevisiae does not induce cellular stress and does not burden the cellular secretory machinery. There are only small changes in the cellular proteome of yeast secreting CALR at a high level.

A comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics

In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics was unfolded with the introduction of dozens of novel instruments that incorporate additional data dimensions through innovative acquisition methodologies, in turn inspiring specialized data analysis pipelines. Simultaneously, a growing number of proteomics datasets have been made publicly available through data repositories such as ProteomeXchange, Zenodo and Skyline Panorama. However, developing algorithms to mine this data and assessing the performance on different platforms is currently hampered by the lack of a single benchmark experimental design. Therefore, we acquired a hybrid proteome mixture on different instrument platforms and in all currently available families of data acquisition. Here, we present a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset acquired using several of the most commonly used current day instrumental platforms. The dataset consists of over 700 LC-MS runs, including adequate replicates allowing robust statistics and covering over nearly 10 different data formats, including scanning quadrupole and ion mobility enabled acquisitions. Datasets are available via ProteomeXchange (PXD028735).

Measurement(s)	Digital Data Repository
Technology Type(s)	Digital Data Repository

Progressive axonopathy when oligodendrocytes lack the myelin protein CMTM5

Oligodendrocytes facilitate rapid impulse propagation along the axons they myelinate and support their long-term integrity. However, the functional relevance of many myelin proteins has remained unknown. Here, we find that expression of the tetraspan-transmembrane protein CMTM5 (chemokine-like factor-like MARVEL-transmembrane domain containing protein 5) is highly enriched in oligodendrocytes and central nervous system (CNS) myelin. Genetic disruption of the Cmtm5 gene in oligodendrocytes of mice does not impair the development or ultrastructure of CNS myelin. However, oligodendroglial Cmtm5 deficiency causes an early-onset progressive axonopathy, which we also observe in global and tamoxifen-induced oligodendroglial Cmtm5 mutants. Presence of the Wld^S mutation ameliorates the axonopathy, implying a Wallerian degeneration-like pathomechanism. These results indicate that CMTM5 is involved in the function of oligodendrocytes to maintain axonal integrity rather than myelin biogenesis.

White matter integrity in mice requires continuous myelin synthesis at the inner tongue

Myelin, the electrically insulating sheath on axons, undergoes dynamic changes over time. However, it is composed of proteins with long lifetimes. This raises the question how such a stable structure is renewed. Here, we study the integrity of myelinated tracts after experimentally preventing the formation of new myelin in the CNS of adult mice, using an inducible Mbp null allele. Oligodendrocytes survive recombination, continue to express myelin genes, but they fail to maintain compacted myelin sheaths. Using 3D electron microscopy and mass spectrometry imaging we visualize myelin-like membranes failing to incorporate adaxonally, most prominently at juxta-paranodes. Myelinoid body formation indicates degradation of existing myelin at the abaxonal side and the inner tongue of the sheath. Thinning of compact myelin and shortening of internodes result in the loss of about 50% of myelin and axonal pathology within 20 weeks post recombination. In summary, our data suggest that functional axon-myelin units require the continuous incorporation of new myelin membranes.

Myelin is formed of proteins of long half-lives. The mechanisms of renewal of such a stable structure are unclear. Here, the authors show that myelin integrity requires continuous myelin synthesis at the inner tongue, contributing to the maintenance of a functional axon-myelin unit.

Effects of Essential Amino Acid Deficiency on General Control Nonderepressible 2/Eukaryotic Initiation Factor 2 Signaling and Proteomic Changes in Primary Bovine Mammary Epithelial Cells

We hypothesized that the general control nonderepressible 2 (GCN2)/eukaryotic initiation factor 2 (eIF2) signaling pathway and intracellular protein synthesis (PS) are regulated to maintain milk PS in primary bovine mammary epithelial cells (MECs) under essential amino acid (EAA) starvation conditions. We cultured MECs with 0%, 2% (depletion), and 100% (control) EAA for two exposure times (8 and 24 h), followed by three refeeding (RF) times with 100% EAA (0, 8, and 24 h). Subsequently, we measured cell viability, total protein concentration, and proliferation. Western blotting was used to quantify the levels of casein and the expression of total GCN2 and eIF2, as well as phosphorylated GCN2 (GCN2P) and eIF2 (eIF2P). The ISOQuant method was used to assess MEC proteomes, and the resultant data were analyzed using the Kruskal−Wallis test, nonpaired Wilcoxon rank post-hoc test, and ANOVA−Tukey test, as well as principal component analyses and multiple regressions models. Differences in cell viability were observed between the control versus the depleted and repleted MECs, respectively, where 97.2−99.8% viability indicated low cell death rates. Proliferation (range, 1.02−1.55 arbitrary units (AU)) was affected by starvation for 12 and 24 h and repletion for 24 h, but it was not increased compared with the control. Total protein expression was unaffected by both depletion and repletion treatments (median 3158 µg/mL). eIF2P expression was significantly increased (p < 0.05) after treatment with 2% EAA for 8 and 24 h compared with 2% EAA with 8 h + 24 h RF and 2% EAA with 24 h + 8 h RF. GCN2P also showed significantly increased expression (p < 0.05) after treatment with 2% EAA for 24 h compared with the control and 2% EAA with 24 h + 8 h RF. Intracellular casein/α-tubulin expression was unaffected by 2% EAA compared with control (0.073 ± 0.01 AU versus 0.086 ± 0.02 AU, respectively). We studied 30 of the detected 1180 proteins, 16 of which were differentially expressed in starved and refed MECs. Cells faced with EAA deficiency activated the GCN2P/eIF2P pathway, and the lack of change in the levels of casein and other milk proteins suggested that the EAA deficit was mitigated by metabolic flexibility to maintain homeostasis.

High-throughput proteomics of nanogram-scale samples with Zeno SWATH MS

The possibility to record proteomes in high throughput and at high quality has opened new avenues for biomedical research, drug discovery, systems biology, and clinical translation. However, high-throughput proteomic experiments often require high sample amounts and can be less sensitive compared to conventional proteomic experiments. Here, we introduce and benchmark Zeno SWATH MS, a data-independent acquisition technique that employs a linear ion trap pulsing (Zeno trap pulsing) to increase the sensitivity in high-throughput proteomic experiments. We demonstrate that when combined with fast micro- or analytical flow-rate chromatography, Zeno SWATH MS increases protein identification with low sample amounts. For instance, using 20 min micro-flow-rate chromatography, Zeno SWATH MS identified more than 5000 proteins consistently, and with a coefficient of variation of 6%, from a 62.5 ng load of human cell line tryptic digest. Using 5 min analytical flow-rate chromatography (800 µl/min), Zeno SWATH MS identified 4907 proteins from a triplicate injection of 2 µg of a human cell lysate, or more than 3000 proteins from a 250 ng tryptic digest. Zeno SWATH MS hence facilitates sensitive high-throughput proteomic experiments with low sample amounts, mitigating the current bottlenecks of high-throughput proteomics.

Analysis of the Human Pineal Proteome by Mass Spectrometry

The human pineal gland regulates the day-night dynamics of multiple physiological processes, especially through the secretion of melatonin. Recently, using mass spectrometry-based proteomics and dedicated analysis tools, we have identified regulated proteins and signaling pathways that differ between day and night and/or between control and autistic pineal glands. This large-scale proteomic approach is the method of choice to study proteins in a biological system globally. This chapter proposes a protocol for large-scale analysis of the pineal gland proteome.

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.

Label-Free Proteomics of Quantity-Limited Samples Using Ion Mobility-Assisted Data-Independent Acquisition Mass Spectrometry

Over the past two decades, unbiased data-independent acquisition (DIA) approaches have gained increasing popularity in the bottom-up proteomics field. Here, we describe an ion mobility separation enhanced DIA workflow for large-scale label-free quantitative proteomics studies where starting material is limited. We set a special focus on the single pot solid-phase-enhanced sample preparation (SP3) protocol, which is well suited for the processing of quantity-limited samples.

RobNorm: model-based robust normalization method for labeled quantitative mass spectrometry proteomics data

MOTIVATION

Data normalization is an important step in processing proteomics data generated in mass spectrometry experiments, which aims to reduce sample-level variation and facilitate comparisons of samples. Previously published methods for normalization primarily depend on the assumption that the distribution of protein expression is similar across all samples. However, this assumption fails when the protein expression data is generated from heterogenous samples, such as from various tissue types. This led us to develop a novel data-driven method for improved normalization to correct the systematic bias meanwhile maintaining underlying biological heterogeneity.

RESULTS

To robustly correct the systematic bias, we used the density-power-weight method to down-weigh outliers and extended the one-dimensional robust fitting method described in the previous work to our structured data. We then constructed a robustness criterion and developed a new normalization algorithm, called RobNorm.In simulation studies and analysis of real data from the genotype-tissue expression project, we compared and evaluated the performance of RobNorm against other normalization methods. We found that the RobNorm approach exhibits the greatest reduction in systematic bias while maintaining across-tissue variation, especially for datasets from highly heterogeneous samples.

AVAILABILITYAND IMPLEMENTATION

https://github.com/mwgrassgreen/RobNorm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Amino Acid Metabolomic Profiles in Bovine Mammary Epithelial Cells under Essential Amino Acid Restriction

Simple Summary

Cells of the mammary gland obtain their necessary nutrients from the blood to produce milk components, such as casein. To achieve higher productivity, cows are excessively supplemented, thus generating a higher cost of production and affecting the environment. Therefore, this triggers the need for a reduction in the supplementation of essential amino acids without affecting the milk composition. The present in vitro study shows that, through homeostatic and homeorhetic processes, cells have the ability to maintain stable casein levels despite decreasing the percentage of essential amino acids (EAAs) supplied. These findings could contribute to the proposal of more efficient nutritional strategies at lower environmental and economic costs.

Abstract

Mammary epithelial cells (MECs) in culture are a useful model for elucidating mammary gland metabolism and changes that occur under different nutrient disponibility. MECs were exposed to different treatments: 100% EAA for 8 h and 24 h restriction (R); 2% EAA for 8 h and 24 h R; 2% EAA for 8 h and 24 h + 100% EAA for 8 h and 24 h restriction + re-feeding (R + RF). Western blotting and protein quantification was performed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) software identified the amino acids (AAs) and signaling pathways. The chi-squared test, multiple classification analysis, and analysis of variance were used for the purification and identification of data. Intracellular casein levels were not affected. The KEGG analysis revealed that the important pathways of metabolism of AAs, which were involved in processes related to metabolism and biosynthesis of phenylalanine, tyrosine, and tryptophan (fumarate, acetyl-CoA, and tricarboxylic acid (TCA) cycle), were affected by both R and R + RF treatments, mainly through the glutamic-oxaloacetic transaminase-2 enzyme. Additionally, metabolic processes mediated by the mitochondrial malate dehydrogenase, S-adenosylmethionine synthetase, and asparagine synthase proteins positively regulated the carbohydrate pathway, pyruvate, and TCA cycles, as well as the metabolism of alanine, aspartate, and glutamate metabolism (carbohydrate and TCA cycle). We hypothesized that MECs have the capacity to utilize alternative pathways that ensure the availability of substrates for composing milk proteins.

Proteome Profile of Myelin in the Zebrafish Brain

The velocity of nerve conduction along vertebrate axons depends on their ensheathment with myelin. Myelin membranes comprise specialized proteins well characterized in mice. Much less is known about the protein composition of myelin in non-mammalian species. Here, we assess the proteome of myelin biochemically purified from the brains of adult zebrafish (Danio rerio), considering its increasing popularity as model organism for myelin biology. Combining gel-based and gel-free proteomic approaches, we identified > 1,000 proteins in purified zebrafish myelin, including all known constituents. By mass spectrometric quantification, the predominant Ig-CAM myelin protein zero (MPZ/P0), myelin basic protein (MBP), and the short-chain dehydrogenase 36K constitute 12%, 8%, and 6% of the total myelin protein, respectively. Comparison with previously established mRNA-abundance profiles shows that expression of many myelin-related transcripts coincides with the maturation of zebrafish oligodendrocytes. Zebrafish myelin comprises several proteins that are not present in mice, including 36K, CLDNK, and ZWI. However, a surprisingly large number of ortholog proteins is present in myelin of both species, indicating partial evolutionary preservation of its constituents. Yet, the relative abundance of CNS myelin proteins can differ markedly as exemplified by the complement inhibitor CD59 that constitutes 5% of the total zebrafish myelin protein but is a low-abundant myelin component in mice. Using novel transgenic reporter constructs and cryo-immuno electron microscopy, we confirm the incorporation of CD59 into myelin sheaths. These data provide the first proteome resource of zebrafish CNS myelin and demonstrate both similarities and heterogeneity of myelin composition between teleost fish and rodents.

Comparative Proteomic Analyses Between Biofilm-Forming and Non-biofilm-Forming Strains of Corynebacterium pseudotuberculosis Isolated From Goats

Caseous lymphadenitis (CLA) is a chronic disease that affects small ruminants and causes economic losses in the associated breeding system. The causative agent of CLA is Corynebacterium pseudotuberculosis, a Gram-positive bacterium that exhibits tropism for external and internal lymph nodes and induces abscess formation in the host. Bacterial communities often produce a biofilm matrix that serves various functions, including protection against hostile environmental conditions, antibiotics, and the host immune response. Although biofilm formation has been reported for C. pseudotuberculosis, not all strains demonstrate this property in culture. In this work, we report the first comparative proteomic analysis of one biofilm-forming (CAPJ4) and one biofilm-non-forming strain (CAP3W) of C. pseudotuberculosis isolated from goats. Bacterial whole cell protein extracts were obtained for mass spectrometry analyses. Using LC-MS/MS, our studies reveal three and four proteins exclusively found in the CAPJ4 and CAP3W proteome, respectively. In addition, label-free quantitative analysis identified 40 proteins showing at-least 2-fold higher values in CAPJ4 compared CAP3W proteome Notably, CAPJ4 differentially synthesized the penicillin-binding protein, which participates in the formation of peptidoglycans. CAPJ4 also exhibited upregulation of N-acetylmuramoyl-L-alanine amidase and galactose-1-phosphate uridylyltransferase, which are involved in biofilm formation and exopolysaccharide biosynthesis. Here, we demonstrate that biofilm formation in C. pseudotuberculosis is likely associated with specific proteins, some of which were previously shown to be associated with virulence and biofilm formation in other organisms. Our findings may drive studies related to the bacterial mechanisms involved in the biofilm formation, in addition to providing targets for the treatment of CLA.

Activity-Based Protein Profiling of Retaining α-Amylases in Complex Biological Samples

Amylases are key enzymes in the processing of starch in many kingdoms of life. They are important catalysts in industrial biotechnology where they are applied in, among others, food processing and the production of detergents. In man amylases are the first enzymes in the digestion of starch to glucose and arguably also the preferred target in therapeutic strategies aimed at the treatment of type 2 diabetes patients through down-tuning glucose assimilation. Efficient and sensitive assays that report selectively on retaining amylase activities irrespective of the nature and complexity of the biomaterial studied are of great value both in finding new and effective human amylase inhibitors and in the discovery of new microbial amylases with potentially advantageous features for biotechnological application. Activity-based protein profiling (ABPP) of retaining glycosidases is inherently suited for the development of such an assay format. We here report on the design and synthesis of 1,6-epi-cyclophellitol-based pseudodisaccharides equipped with a suite of reporter entities and their use in ABPP of retaining amylases from human saliva, murine tissue as well as secretomes from fungi grown on starch. The activity and efficiency of the inhibitors and probes are substantiated by extensive biochemical analysis, and the selectivity for amylases over related retaining endoglycosidases is validated by structural studies.

Use of Hybrid Data-Dependent and -Independent Acquisition Spectral Libraries Empowers Dual-Proteome Profiling

In the context of bacterial infections, it is imperative that physiological responses can be studied in an integrated manner, meaning a simultaneous analysis of both the host and the pathogen responses. To improve the sensitivity of detection, data-independent acquisition (DIA)-based proteomics was found to outperform data-dependent acquisition (DDA) workflows in identifying and quantifying low-abundant proteins. Here, by making use of representative bacterial pathogen/host proteome samples, we report an optimized hybrid library generation workflow for DIA mass spectrometry relying on the use of data-dependent and in silico-predicted spectral libraries. When compared to searching DDA experiment-specific libraries only, the use of hybrid libraries significantly improved peptide detection to an extent suggesting that infection-relevant host-pathogen conditions could be profiled in sufficient depth without the need of a priori bacterial pathogen enrichment when studying the bacterial proteome. Proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD017904 and PXD017945.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

The CNS Myelin Proteome: Deep Profile and Persistence After Post-mortem Delay

Myelin membranes are dominated by lipids while the complexity of their protein composition has long been considered to be low. However, numerous additional myelin proteins have been identified since. Here we revisit the proteome of myelin biochemically purified from the brains of healthy c56Bl/6N-mice utilizing complementary proteomic approaches for deep qualitative and quantitative coverage. By gel-free, label-free mass spectrometry, the most abundant myelin proteins PLP, MBP, CNP, and MOG constitute 38, 30, 5, and 1% of the total myelin protein, respectively. The relative abundance of myelin proteins displays a dynamic range of over four orders of magnitude, implying that PLP and MBP have overshadowed less abundant myelin constituents in initial gel-based approaches. By comparisons with published datasets we evaluate to which degree the CNS myelin proteome correlates with the mRNA and protein abundance profiles of myelin and oligodendrocytes. Notably, the myelin proteome displays only minor changes if assessed after a post-mortem delay of 6 h. These data provide the most comprehensive proteome resource of CNS myelin so far and a basis for addressing proteomic heterogeneity of myelin in mouse models and human patients with white matter disorders.

Anatomy and evolution of database search engines-a central component of mass spectrometry based proteomic workflows

Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines.

Proteome profile of peripheral myelin in healthy mice and in a neuropathy model

Proteome and transcriptome analyses aim at comprehending the molecular profiles of the brain, its cell-types and subcellular compartments including myelin. Despite the relevance of the peripheral nervous system for normal sensory and motor capabilities, analogous approaches to peripheral nerves and peripheral myelin have fallen behind evolving technical standards. Here we assess the peripheral myelin proteome by gel-free, label-free mass-spectrometry for deep quantitative coverage. Integration with RNA-Sequencing-based developmental mRNA-abundance profiles and neuropathy disease genes illustrates the utility of this resource. Notably, the periaxin-deficient mouse model of the neuropathy Charcot-Marie-Tooth 4F displays a highly pathological myelin proteome profile, exemplified by the discovery of reduced levels of the monocarboxylate transporter MCT1/SLC16A1 as a novel facet of the neuropathology. This work provides the most comprehensive proteome resource thus far to approach development, function and pathology of peripheral myelin, and a straightforward, accurate and sensitive workflow to address myelin diversity in health and disease.

STA-55, an Easily Accessible, Broad-Spectrum, Activity-Based Aldehyde Dehydrogenase Probe

Aldehyde dehydrogenases (ALDHs) convert aldehydes into carboxylic acids and are often upregulated in cancer. They have been linked to therapy resistance and are therefore potential therapeutic targets. However, only a few selective and potent inhibitors are currently available for this group of enzymes. Competitive activity-based protein profiling (ABPP) would aid the development and validation of new selective inhibitors. Herein, a broad-spectrum activity-based probe that reports on several ALDHs is presented. This probe was used in a competitive ABPP protocol against three ALDH inhibitors in lung cancer cells to determine their selectivity profiles and establish their target engagement.

Molecular Insights into miRNA-Driven Resistance to 5-Fluorouracil and Oxaliplatin Chemotherapy: miR-23b Modulates the Epithelial–Mesenchymal Transition of Colorectal Cancer Cells

Although treatment of colorectal cancer with 5-florouracil and oxaliplatin is widely used, it is frequently followed by a relapse. Therefore, there is an urgent need for profound understanding of chemotherapy resistance mechanisms as well as the profiling of predictive markers for individualized treatment. In this study, we identified the changes in 14 miRNAs in 5-fluouracil and 40 miRNAs in oxaliplatin-resistant cell lines by miRNA sequencing. The decrease in miR-224-5p expression in the 5-fluorouracil-resistant cells correlated with drug insensitivity due to its overexpression-induced drug-dependent apoptosis. On the other hand, the miR-23b/27b/24-1 cluster was overexpressed in oxaliplatin-resistant cells. The knockout of miR-23b led to the partial restoration of oxaliplatin susceptibility, showing the essential role of miR-23b in the development of drug resistance by this cluster. Proteomic analysis identified target genes of miR-23b and showed that endothelial–mesenchymal transition (EMT) was implicated in oxaliplatin insensibility. Data revealed that EMT markers, such as vimentin and SNAI2, were expressed moderately higher in the oxaliplatin-resistant cells and their expression increased further in the less drug-resistant cells, which had miR-23b knockout. This establishes that the balance of EMT contributes to the drug resistance, showing the importance of the miR-23b-mediated fine-tuning of EMT in oxaliplatin-resistant cancer cells.

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.

Vti1b promotes TRPV1 sensitization during inflammatory pain

Sensitization of the transient receptor potential ion channel vanilloid 1 (TRPV1) is critically involved in inflammatory pain. To date, manifold signaling cascades have been shown to converge onto TRPV1 and enhance its sensitization. However, many of them also play a role for nociceptive pain, which limits their utility as targets for therapeutic intervention. Here, we show that the vesicle transport through interaction with t-SNAREs homolog 1B (Vti1b) protein promotes TRPV1 sensitization upon inflammation in cell culture but leaves normal functioning of TRPV1 intact. Importantly, the effect of Vti1b can be recapitulated in vivo: Virus-mediated knockdown of Vti1b in sensory neurons attenuated thermal hypersensitivity during inflammatory pain without affecting mechanical hypersensitivity or capsaicin-induced nociceptive pain. Interestingly, TRPV1 and Vti1b are localized in close vicinity as indicated by proximity ligation assays and are likely to bind to each other, either directly or indirectly, as suggested by coimmunoprecipitations. Moreover, using a mass spectrometry-based quantitative interactomics approach, we show that Vti1b is less abundant in TRPV1 protein complexes during inflammatory conditions compared with controls. Alongside, we identify numerous novel and pain state-dependent binding partners of native TRPV1 in dorsal root ganglia. These data represent a unique resource on the dynamics of the TRPV1 interactome and facilitate mechanistic insights into TRPV1 regulation. We propose that inflammation-related differences in the TRPV1 interactome identified here could be exploited to specifically target inflammatory pain in the future.

Myelinating Glia-Specific Deletion of Fbxo7 in Mice Triggers Axonal Degeneration in the Central Nervous System Together with Peripheral Neuropathy

Myelination of axons facilitates the rapid propagation of electrical signals and the long-term integrity of axons. The ubiquitin-proteasome system is essential for proper protein homeostasis, which is particularly crucial for interactions of postmitotic cells. In our study, we examined how the E3 ubiquitin ligase FBXO7-SCF (SKP1, Cul1, F-box protein) expressed in myelinating cells affects the axon-myelin unit. Deletion of Fbxo7 in oligodendrocytes and Schwann cells in mice using the Cnp1-Cre driver line led to motor impairment due to hindlimb paresis. It did not result in apoptosis of myelinating cells, nor did it affect the proper myelination of axons or lead to demyelination. It however triggered axonal degeneration in the CNS and resulted in the severe degeneration of axons in the PNS, inducing a full-blown neuropathy. Both the CNS and PNS displayed inflammation, while the PNS was also characterized by fibrosis, massive infiltration of macrophages, and edema. Tamoxifen-induced deletion of Fbxo7, after myelination using the Plp1-CreERT2 line, led to a small number of degenerated axons and hence a very mild peripheral neuropathy. Interestingly, loss of Fbxo7 also resulted in reduced proteasome activity in Schwann cells but not in cerebellar granule neurons, indicating a specific sensitivity of the former cell type. Together, our results demonstrate an essential role for FBXO7 in myelinating cells to support associated axons, which is fundamental to the proper developmental establishment and the long-term integrity of the axon-myelin unit.SIGNIFICANCE STATEMENT The myelination of axons facilitates the fast propagation of electrical signals and the trophic support of the myelin-axon unit. Here, we report that deletion of Fbxo7 in myelinating cells in mice triggered motor impairment but had no effect on myelin biogenesis. Loss of Fbxo7 in myelinating glia, however, led to axonal degeneration in the CNS and peripheral neuropathy of the axonal type. In addition, we found that Schwann cells were particularly sensitive to Fbxo7 deficiency reflected by reduced proteasome activity. Based on these findings, we conclude that Fbxo7 is essential for the support of the axon-myelin unit and long-term axonal health.

Anillin facilitates septin assembly to prevent pathological outfoldings of central nervous system myelin

Myelin serves as an axonal insulator that facilitates rapid nerve conduction along axons. By transmission electron microscopy, a healthy myelin sheath comprises compacted membrane layers spiraling around the cross-sectioned axon. Previously we identified the assembly of septin filaments in the innermost non-compacted myelin layer as one of the latest steps of myelin maturation in the central nervous system (CNS) (Patzig et al., 2016). Here we show that loss of the cytoskeletal adaptor protein anillin (ANLN) from oligodendrocytes disrupts myelin septin assembly, thereby causing the emergence of pathological myelin outfoldings. Since myelin outfoldings are a poorly understood hallmark of myelin disease and brain aging we assessed axon/myelin-units in Anln-mutant mice by focused ion beam-scanning electron microscopy (FIB-SEM); myelin outfoldings were three-dimensionally reconstructed as large sheets of multiple compact membrane layers. We suggest that anillin-dependent assembly of septin filaments scaffolds mature myelin sheaths, facilitating rapid nerve conduction in the healthy CNS.

Delineation of the pan-proteome of fish-pathogenic Streptococcus agalactiae strains using a label-free shotgun approach

BACKGROUND

Streptococcus agalactiae (GBS) is a major pathogen of Nile tilapia, a global commodity of the aquaculture sector. The aims of this study were to evaluate protein expression in the main genotypes of GBS isolated from diseased fishes in Brazil using a label-free shotgun nano-liquid chromatography-ultra definition mass spectrometry (nanoLC-UDMS^E) approach and to compare the differential abundance of proteins identified in strains isolated from GBS-infected fishes and humans.

RESULTS

A total of 1070 protein clusters were identified by nanoLC-UDMS^E in 5 fish-adapted GBS strains belonging to sequence types ST-260 and ST-927 and the non-typeable (NT) lineage and 1 human GBS strain (ST-23). A total of 1065 protein clusters corresponded to the pan-proteome of fish-adapted GBS strains; 989 of these were identified in all fish-adapted GBS strains (core proteome), and 62 were shared by at least two strains (accessory proteome). Proteins involved in the stress response and in the regulation of gene expression, metabolism and virulence were detected, reflecting the adaptive ability of fish-adapted GBS strains in response to stressor factors that affect bacterial survival in the aquatic environment and bacterial survival and multiplication inside the host cell. Measurement of protein abundance among different hosts showed that 5 and 26 proteins were exclusively found in the human- and fish-adapted GBS strains, respectively; the proteins exclusively identified in fish isolates were mainly related to virulence factors. Furthermore, 215 and 269 proteins were up- and down-regulated, respectively, in the fish-adapted GBS strains in comparison to the human isolate.

CONCLUSIONS

Our study showed that the core proteome of fish-adapted GBS strains is conserved and demonstrated high similarity of the proteins expressed by fish-adapted strains to the proteome of the human GBS strain. This high degree of proteome conservation of different STs suggests that, a monovalent vaccine may be effective against these variants.

Transcriptome and Proteome of Fish-Pathogenic Streptococcus agalactiae Are Modulated by Temperature

Streptococcus agalactiae is one of the most important pathogens associated with streptococcosis outbreaks in Nile tilapia farms worldwide. High water temperature (above 27°C) has been described as a predisposing factor for the disease in fish. At low temperatures (below 25°C), fish mortalities are not usually observed in farms. Temperature variation can modulate the expression of genes and proteins involved in metabolism, adaptation, and bacterial pathogenicity, thus increasing or decreasing the ability to infect the host. This study aimed to evaluate the transcriptome and proteome of a fish-pathogenic S. agalactiae strain SA53 subjected to in vitro growth at different temperatures using a microarray and label-free shotgun LC-HDMS^E approach. Biological triplicates of isolates were cultured in BHIT broth at 22 or 32°C for RNA and protein isolation and submitted for transcriptomic and proteomic analyses. In total, 1,730 transcripts were identified in SA53, with 107 genes being differentially expressed between the temperatures evaluated. A higher number of genes related to metabolism, mainly from the phosphotransferase system (PTS) and ATP-binding cassette (ABC) transport system, were upregulated at 32°C. In the proteome analysis, 1,046 proteins were identified in SA53, of which 81 were differentially regulated between 22 and 32°C. Proteins involved in defense mechanisms, lipid transport and metabolism, and nucleotide transport and metabolism were upregulated at 32°C. A higher number of interactions were observed in proteins involved in nucleotide transport and metabolism. We observed a low correlation between the transcriptome and proteome datasets. Our study indicates that the transcriptome and proteome of a fish-adapted S. agalactiae strain are modulated by temperature, particularly showing differential expression of genes/proteins involved in metabolism, virulence factors, and adaptation.

In Search of Biomarkers for Pathogenesis and Control of Leishmaniasis by Global Analyses of Leishmania-Infected Macrophages

Leishmaniasis is a vector-borne, neglected tropical disease with a worldwide distribution that can present in a variety of clinical forms, depending on the parasite species and host genetic background. The pathogenesis of this disease remains far from being elucidated because the involvement of a complex immune response orchestrated by host cells significantly affects the clinical outcome. Among these cells, macrophages are the main host cells, produce cytokines and chemokines, thereby triggering events that contribute to the mediation of the host immune response and, subsequently, to the establishment of infection or, alternatively, disease control. There has been relatively limited commercial interest in developing new pharmaceutical compounds to treat leishmaniasis. Moreover, advances in the understanding of the underlying biology of Leishmania spp. have not translated into the development of effective new chemotherapeutic compounds. As a result, biomarkers as surrogate disease endpoints present several potential advantages to be used in the identification of targets capable of facilitating therapeutic interventions considered to ameliorate disease outcome. More recently, large-scale genomic and proteomic analyses have allowed the identification and characterization of the pathways involved in the infection process in both parasites and the host, and these analyses have been shown to be more effective than studying individual molecules to elucidate disease pathogenesis. RNA-seq and proteomics are large-scale approaches that characterize genes or proteins in a given cell line, tissue, or organism to provide a global and more integrated view of the myriad biological processes that occur within a cell than focusing on an individual gene or protein. Bioinformatics provides us with the means to computationally analyze and integrate the large volumes of data generated by high-throughput sequencing approaches. The integration of genomic expression and proteomic data offers a rich multi-dimensional analysis, despite the inherent technical and statistical challenges. We propose that these types of global analyses facilitate the identification, among a large number of genes and proteins, those that hold potential as biomarkers. The present review focuses on large-scale studies that have identified and evaluated relevant biomarkers in macrophages in response to Leishmania infection.

Mutation of the Surface Layer Protein SlpB Has Pleiotropic Effects in the Probiotic Propionibacterium freudenreichii CIRM-BIA 129

Propionibacterium freudenreichii is a beneficial Gram-positive bacterium, traditionally used as a cheese-ripening starter, and currently considered as an emerging probiotic. As an example, the P. freudenreichii CIRM-BIA 129 strain recently revealed promising immunomodulatory properties. Its consumption accordingly exerts healing effects in different animal models of colitis, suggesting a potent role in the context of inflammatory bowel diseases. This anti-inflammatory effect depends on surface layer proteins (SLPs). SLPs may be involved in key functions in probiotics, such as persistence within the gut, adhesion to host cells and mucus, or immunomodulation. Several SLPs coexist in P. freudenreichii CIRM-BIA 129 and mediate immunomodulation and adhesion. A mutant P. freudenreichii CIRM-BIA 129ΔslpB (CB129ΔslpB) strain was shown to exhibit decreased adhesion to intestinal epithelial cells. In the present study, we thoroughly analyzed the impact of this mutation on cellular properties. Firstly, we investigated alterations of surface properties in CB129ΔslpB. Surface extractable proteins, surface charges (ζ-potential) and surface hydrophobicity were affected by the mutation. Whole-cell proteomics, using high definition mass spectrometry, identified 1,288 quantifiable proteins in the wild-type strain, i.e., 53% of the theoretical proteome predicted according to P. freudenreichii CIRM-BIA 129 genome sequence. In the mutant strain, we detected 1,252 proteins, including 1,227 proteins in common with the wild-type strain. Comparative quantitative analysis revealed 97 proteins with significant differences between wild-type and mutant strains. These proteins are involved in various cellular process like signaling, metabolism, and DNA repair and replication. Finally, in silico analysis predicted that slpB gene is not part of an operon, thus not affecting the downstream genes after gene knockout. This study, in accordance with the various roles attributed in the literature to SLPs, revealed a pleiotropic effect of a single slpB mutation, in the probiotic P. freudenreichii. This suggests that SlpB may be at a central node of cellular processes and confirms that both nature and amount of SLPs, which are highly variable within the P. freudenreichii species, determine the probiotic abilities of strains.

SUMO1-conjugation is altered during normal aging but not by increased amyloid burden

A proper equilibrium of post-translational protein modifications is essential for normal cell physiology, and alteration in these processes is key in neurodegenerative disorders such as Alzheimer's disease. Recently, for instance, alteration in protein SUMOylation has been linked to amyloid pathology. In this work, we aimed to elucidate the role of protein SUMOylation during aging and increased amyloid burden in vivo using a His₆ -HA-SUMO1 knock-in mouse in the 5XFAD model of Alzheimer's disease. Interestingly, we did not observe any alteration in the levels of SUMO1-conjugation related to Alzheimer's disease. SUMO1 conjugates remained localized to neuronal nuclei upon increased amyloid burden and during aging and were not detected in amyloid plaques. Surprisingly however, we observed age-related alterations in global levels of SUMO1 conjugation and at the level of individual substrates using quantitative proteomic analysis. The identified SUMO1 candidate substrates are dominantly nuclear proteins, mainly involved in RNA processing. Our findings open novel directions of research for studying a functional link between SUMOylation and its role in guarding nuclear functions during aging.

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.

Challenges and Opportunities for Biological Mass Spectrometry Core Facilities in the Developing World

The developing world is seeing rapid growth in the availability of biological mass spectrometry (MS), particularly through core facilities. As proteomics and metabolomics becomes locally feasible for investigators in these nations, application areas associated with high burden in these nations, such as infectious disease, will see greatly increased research output. This article evaluates the rapid growth of MS in South Africa (currently approaching 20 laboratories) as a model for establishing MS core facilities in other nations of the developing world. Facilities should emphasize new services rather than new instruments. The reduction of the delays associated with reagent and other supply acquisition would benefit both facilities and the users who make use of their services. Instrument maintenance and repair, often mediated by an in-country business for an international vendor, is also likely to operate on a slower schedule than in the wealthiest nations. A key challenge to facilities in the developing world is educating potential facility users in how best to design experiments for proteomics and metabolomics, what reagents are most likely to introduce problematic artifacts, and how to interpret results from the facility. Here, we summarize the experience of 6 different institutions to raise the level of biological MS available to researchers in South Africa.

Enhanced differential expression statistics for data-independent acquisition proteomics

We describe a new reproducibility-optimization method ROPECA for statistical analysis of proteomics data with a specific focus on the emerging data-independent acquisition (DIA) mass spectrometry technology. ROPECA optimizes the reproducibility of statistical testing on peptide-level and aggregates the peptide-level changes to determine differential protein-level expression. Using a ‘gold standard’ spike-in data and a hybrid proteome benchmark data we show the competitive performance of ROPECA over conventional protein-based analysis as well as state-of-the-art peptide-based tools especially in DIA data with consistent peptide measurements. Furthermore, we also demonstrate the improved accuracy of our method in clinical studies using proteomics data from a longitudinal human twin study.

The hepatocyte proteome in organotypic rat liver models and the influence of the local microenvironment

BACKGROUND

Liver models that closely mimic the in vivo microenvironment are useful for understanding liver functions, capabilities, and intercellular communication processes. Three-dimensional (3D) liver models assembled using hepatocytes and liver sinusoidal endothelial cells (LSECs) separated by a polyelectrolyte multilayer (PEM) provide a functional system while also permitting isolation of individual cell types for proteomic analyses.

METHODS

To better understand the mechanisms and processes that underlie liver model function, hepatocytes were maintained as monolayers and 3D PEM-based formats in the presence or absence of primary LSECs. The resulting hepatocyte proteomes, the proteins in the PEM, and extracellular levels of urea, albumin and glucose after three days of culture were compared.

RESULTS

All systems were ketogenic and found to release glucose. The presence of the PEM led to increases in proteins associated with both mitochondrial and peroxisomal-based β-oxidation. The PEMs also limited production of structural and migratory proteins associated with dedifferentiation. The presence of LSECs increased levels of Phase I and Phase II biotransformation enzymes as well as several proteins associated with the endoplasmic reticulum and extracellular matrix remodeling. The proteomic analysis of the PEMs indicated that there was no significant change after three days of culture. These results are discussed in relation to liver model function.

CONCLUSIONS

Heterotypic cell-cell and cell-ECM interactions exert different effects on hepatocyte functions and phenotypes.

Towards broad spectrum activity-based glycosidase probes: synthesis and evaluation of deoxygenated cyclophellitol aziridines

Deoxygenated cyclophellitol aziridines enable activity-based inter-class labeling of glycosidases including LC-MS/MS identification.

A multicenter study benchmarks software tools for label-free proteome quantification

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

Testing and Validation of Computational Methods for Mass Spectrometry

High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.