Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

A splice site variant in MADD affects hormone expression in pancreatic β cells and pituitary gonadotropes

MAPK activating death domain (MADD) is a multifunctional protein regulating small GTPases RAB3 and RAB27, MAPK signaling, and cell survival. Polymorphisms in the MADD locus are associated with glycemic traits, but patients with biallelic variants in MADD manifest a complex syndrome affecting nervous, endocrine, exocrine, and hematological systems. We identified a homozygous splice site variant in MADD in 2 siblings with developmental delay, diabetes, congenital hypogonadotropic hypogonadism, and growth hormone deficiency. This variant led to skipping of exon 30 and in-frame deletion of 36 amino acids. To elucidate how this mutation causes pleiotropic endocrine phenotypes, we generated relevant cellular models with deletion of MADD exon 30 (dex30). We observed reduced numbers of β cells, decreased insulin content, and increased proinsulin-to-insulin ratio in dex30 human embryonic stem cell-derived pancreatic islets. Concordantly, dex30 led to decreased insulin expression in human β cell line EndoC-βH1. Furthermore, dex30 resulted in decreased luteinizing hormone expression in mouse pituitary gonadotrope cell line LβT2 but did not affect ontogeny of stem cell-derived GnRH neurons. Protein-protein interactions of wild-type and dex30 MADD revealed changes affecting multiple signaling pathways, while the GDP/GTP exchange activity of dex30 MADD remained intact. Our results suggest MADD-specific processes regulate hormone expression in pancreatic β cells and pituitary gonadotropes.

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host-pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

Glioblastoma biomarkers in urinary extracellular vesicles reveal the potential for a 'liquid gold' biopsy

BACKGROUND

Biomarkers that reflect glioblastoma tumour activity and treatment response are urgently needed to help guide clinical management, particularly for recurrent disease. As the urinary system is a major clearance route of circulating extracellular vesicles (EVs; 30-1000 nm nanoparticles) we explored whether sampling urinary-EVs could serve as a simple and non-invasive liquid biopsy approach for measuring glioblastoma-associated biomarkers.

METHODS

Fifty urine specimens (15-60 ml) were collected from 24 catheterised glioblastoma patients immediately prior to primary (n = 17) and recurrence (n = 7) surgeries, following gross total resection (n = 9), and from age/gender-matched healthy participants (n = 14). EVs isolated by differential ultracentrifugation were characterised and extracted proteomes were analysed by high-resolution data-independent acquisition liquid chromatography tandem mass spectrometry (DIA-LC-MS/MS).

RESULTS

Overall, 6857 proteins were confidently identified in urinary-EVs (q-value ≤ 0.01), including 94 EV marker proteins. Glioblastoma-specific proteomic signatures were determined, and putative urinary-EV biomarkers corresponding to tumour burden and recurrence were identified (FC ≥ | 2 | , adjust p-val≤0.05, AUC > 0.9).

CONCLUSION

In-depth DIA-LC-MS/MS characterisation of urinary-EVs substantiates urine as a viable source of glioblastoma biomarkers. The promising 'liquid gold' biomarker panels described here warrant further investigation.

Proteome dataset of Candida albicans (ATCC10231) opaque cell

OBJECTIVES

Candida albicans, a polymorphic yeast, is one of the most common, opportunistic fungal pathogens of humans. Among the different morphological forms, opaque form is one of the least-studied ones. This opaque phenotype is essential for mating and is also reported to be involved in colonizing the gastrointestinal tract. Considering the significance of the clinical and sexual reproduction of C. albicans, we have investigated the morphophysiological modulations in opaque form using a proteomic approach.

DATA DESCRIPTION

In the current investigation, we have used Micro-Liquid Chromatography-Mass Spectrometry (LC-MS/MS) analysis to create a protein profile for opaque-specific proteins. Whole-cell proteins from C. albicans (ATCC10231) cells that had been cultured for seven days on synthetic complete dextrose (SCD) medium in both as an opaque (test) and as a white (control) form cells were extracted, digested, and identified using LC-MS/MS. This information is meant to serve the scientific community and represents the proteome profile (SWATH Spectral Libraries) of C. albicans opaque form.

Systematic analysis of alternative exon-dependent interactome remodeling reveals multitasking functions of gene regulatory factors

Alternative splicing significantly expands biological complexity, particularly in the vertebrate nervous system. Increasing evidence indicates that developmental and tissue-dependent alternative exons often control protein-protein interactions; yet, only a minor fraction of these events have been characterized. Using affinity purification-mass spectrometry (AP-MS), we show that approximately 60% of analyzed neural-differential exons in proteins previously implicated in transcriptional regulation result in the gain or loss of interaction partners, which in some cases form unexpected links with coupled processes. Notably, a neural exon in Chtop regulates its interaction with the Prmt1 methyltransferase and DExD-Box helicases Ddx39b/a, affecting its methylation and activity in promoting RNA export. Additionally, a neural exon in Sap30bp affects interactions with RNA processing factors, modulating a critical function of Sap30bp in promoting the splicing of <100 nt "mini-introns" that control nuclear RNA levels. AP-MS is thus a powerful approach for elucidating the multifaceted functions of proteins imparted by context-dependent alternative exons.

Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape

The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.

Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities

Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.

Label-Free Quantitative Thermal Proteome Profiling Reveals Target Transcription Factors with Activities Modulated by MC3R Signaling

Thermal proteome profiling with label-free quantitation using ion-mobility-enhanced LC-MS offers versatile data sets, providing information on protein differential expression, thermal stability, and the activities of transcription factors. We developed a multidimensional data analysis workflow for label-free quantitative thermal proteome profiling (TPP) experiments that incorporates the aspects of gene set enrichment analysis, differential protein expression analysis, and inference of transcription factor activities from LC-MS data. We applied it to study the signaling processes downstream of melanocortin 3 receptor (MC3R) activation by endogenous agonists derived from the proopiomelanocortin prohormone: ACTH, α-MSH, and γ-MSH. The obtained information was used to map signaling pathways downstream of MC3R and to deduce transcription factors responsible for cellular response to ligand treatment. Using our workflow, we identified differentially expressed proteins and investigated their thermal stability. We found in total 298 proteins with altered thermal stability, resulting from MC3R activation. Out of these, several proteins were transcription factors, indicating them as being downstream target regulators that take part in the MC3R signaling cascade. We found transcription factors CCAR2, DDX21, HMGB2, SRSF7, and TET2 to have altered thermal stability. These apparent target transcription factors within the MC3R signaling cascade play important roles in immune responses. Additionally, we inferred the activities of the transcription factors identified in our data set. This was done with Bayesian statistics using the differential expression data we obtained with label-free quantitative LC-MS. The inferred transcription factor activities were validated in our bioinformatic pipeline by the phosphorylated peptide abundances that we observed, highlighting the importance of post-translational modifications in transcription factor regulation. Our multidimensional data analysis workflow allows for a comprehensive characterization of the signaling processes downstream of MC3R activation. It provides insights into protein differential expression, thermal stability, and activities of key transcription factors. All proteomic data generated in this study are publicly available at DOI: 10.6019/PXD039945.

New Insights on Sperm Function in Male Infertility of Unknown Origin: A Multimodal Approach

The global trend of rising (male) infertility is concerning, and the unidentifiable causes in half of the cases, the so-called unknown origin male infertility (UOMI), demands a better understanding and assessment of both external/internal factors and mechanisms potentially involved. In this work, it was our aim to obtain new insight on UOMI, specifically on idiopathic (ID) and Unexplained male infertility (UMI), relying on a detailed evaluation of the male gamete, including functional, metabolic and proteomic aspects. For this purpose, 1114 semen samples, from males in couples seeking infertility treatment, were collected at the Reproductive Medicine Unit from the Centro Hospitalar e Universitário de Coimbra (CHUC), from July 2018-July 2022. Based on the couples' clinical data, seminal/hormonal analysis, and strict eligibility criteria, samples were categorized in 3 groups, control (CTRL), ID and UMI. Lifestyle factors and anxiety/depression symptoms were assessed via survey. Sperm samples were evaluated functionally, mitochondrially and using proteomics. The results of Assisted Reproduction Techniques were assessed whenever available. According to our results, ID patients presented the worst sperm functional profile, while UMI patients were similar to controls. The proteomic analysis revealed 145 differentially expressed proteins, 8 of which were specifically altered in ID and UMI samples. Acrosin (ACRO) and sperm acrosome membrane-associated protein 4 (SACA4) were downregulated in ID patients while laminin subunit beta-2 (LAMB2), mannose 6-phosphate isomerase (MPI), ATP-dependent 6-phosphofructokinase liver type (PFKAL), STAR domain-containing protein 10 (STA10), serotransferrin (TRFE) and exportin-2 (XPO2) were downregulated in UMI patients. Using random forest analysis, SACA4 and LAMB2 were identified as the sperm proteins with a higher chance of distinguishing ID and UMI patients, and their function and expression variation were in accordance with the functional results. No alterations were observed in terms of lifestyle and psychological factors among the 3 groups. These findings obtained in an experimental setting based on 3 well-defined groups of subjects, might help to validate new biomarkers for unknown origin male infertility (ID and UMI) that, in the future, can be used to improve diagnostics and treatments.

Proteomic dataset of Candida albicans (ATCC 10231) Biofilm

OBJECTIVES

The ability to form biofilm is considered as one of major virulence factors of Candida albicans, as biofilms form growth confers antifungal resistance and facilitate immune evasion. It is intriguing to understand morphophysiological modulations in the C. albicans cells growing under biofilm form growth.

DATA DESCRIPTION

In present study, we have profiled biofilm-specific proteins using LC-MS/MS analysis. Whole cell proteins of C. albicans cells grown under biofilm form growth (test) and planktonic (control) growth for 24 h were extracted, digested and identified using micro-Liquid Chromatography-Mass Spectrometry (LC-MS/MS). The present data represents proteomic profile (SWATH Spectral Libraries) of C. albicans biofilm intended to be useful to scientific community as it exhibits reuse potential.

Biogenic Solution Map Based on the Definition of the Metabolic Correlation Distance between 4-Dimensional Fingerprints

Accurate discrimination and classification of unknown species are the basis to predict its characteristics or applications to make correct decisions. However, for biogenic solutions that are ubiquitous in nature and our daily lives, direct determination of their similarities and disparities by their molecular compositions remains a scientific challenge. Here, we explore a standard and visualizable ontology, termed "biogenic solution map", that organizes multifarious classes of biogenic solutions into a map of hierarchical structures. To build the map, a novel 4-dimensional (4D) fingerprinting method based on data-independent acquisition data sets of untargeted metabolomics is developed, enabling accurate characterization of complex biogenic solutions. A generic parameter of metabolic correlation distance, calculated based on averaged similarities between 4D fingerprints of sample groups, is able to define "species", "genus", and "family" of each solution in the map. With the help of the "biogenic solution map", species of unknown biogenic solutions can be explicitly defined. Simultaneously, intrinsic correlations and subtle variations among biogenic solutions in the map are accurately illustrated. Moreover, it is worth mentioning that samples of the same analyte but prepared by alternative protocols may have significantly different metabolic compositions and could be classified into different "genera".

Identification of Protein Complexes by Integrating Protein Abundance and Interaction Features Using a Deep Learning Strategy

Many essential cellular functions are carried out by multi-protein complexes that can be characterized by their protein-protein interactions. The interactions between protein subunits are critically dependent on the strengths of their interactions and their cellular abundances, both of which span orders of magnitude. Despite many efforts devoted to the global discovery of protein complexes by integrating large-scale protein abundance and interaction features, there is still room for improvement. Here, we integrated >7000 quantitative proteomic samples with three published affinity purification/co-fractionation mass spectrometry datasets into a deep learning framework to predict protein-protein interactions (PPIs), followed by the identification of protein complexes using a two-stage clustering strategy. Our deep-learning-technique-based classifier significantly outperformed recently published machine learning prediction models and in the process captured 5010 complexes containing over 9000 unique proteins. The vast majority of proteins in our predicted complexes exhibited low or no tissue specificity, which is an indication that the observed complexes tend to be ubiquitously expressed throughout all cell types and tissues. Interestingly, our combined approach increased the model sensitivity for low abundant proteins, which amongst other things allowed us to detect the interaction of MCM10, which connects to the replicative helicase complex via the MCM6 protein. The integration of protein abundances and their interaction features using a deep learning approach provided a comprehensive map of protein-protein interactions and a unique perspective on possible novel protein complexes.

Glial-Restricted Precursors stimulate endogenous cytogenesis and effectively recover emotional deficits in a model of cytogenesis ablation

Adult cytogenesis, the continuous generation of newly-born neurons (neurogenesis) and glial cells (gliogenesis) throughout life, is highly impaired in several neuropsychiatric disorders, such as Major Depressive Disorder (MDD), impacting negatively on cognitive and emotional domains. Despite playing a critical role in brain homeostasis, the importance of gliogenesis has been overlooked, both in healthy and diseased states. To examine the role of newly formed glia, we transplanted Glial Restricted Precursors (GRPs) into the adult hippocampal dentate gyrus (DG), or injected their secreted factors (secretome), into a previously validated transgenic GFAP-tk rat line, in which cytogenesis is transiently compromised. We explored the long-term effects of both treatments on physiological and behavioral outcomes. Grafted GRPs reversed anxiety-like and depressive-like deficits, while the secretome promoted recovery of only anxiety-like behavior. Furthermore, GRPs elicited a recovery of neurogenic and gliogenic levels in the ventral DG, highlighting the unique involvement of these cells in the regulation of brain cytogenesis. Both GRPs and their secretome induced significant alterations in the DG proteome, directly influencing proteins and pathways related to cytogenesis, regulation of neural plasticity and neuronal development. With this work, we demonstrate a valuable and specific contribution of glial progenitors to normalizing gliogenic levels, rescueing neurogenesis and, importantly, promoting recovery of emotional deficits characteristic of disorders such as MDD.

A central chaperone-like role for 14-3-3 proteins in human cells

14-3-3 proteins are highly conserved regulatory proteins that interact with hundreds of structurally diverse clients and act as central hubs of signaling networks. However, how 14-3-3 paralogs differ in specificity and how they regulate client protein function are not known for most clients. Here, we map the interactomes of all human 14-3-3 paralogs and systematically characterize the effect of disrupting these interactions on client localization. The loss of 14-3-3 binding leads to the coalescence of a large fraction of clients into discrete foci in a client-specific manner, suggesting a central chaperone-like function for 14-3-3 proteins. Congruently, the engraftment of 14-3-3 binding motifs to nonclients can suppress their aggregation or phase separation. Finally, we show that 14-3-3s negatively regulate the localization of the RNA-binding protein SAMD4A to cytoplasmic granules and inhibit its activity as a translational repressor. Our work suggests that 14-3-3s have a more prominent role as chaperone-like molecules than previously thought.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

NeuroLINCS Proteomics: Defining human-derived iPSC proteomes and protein signatures of pluripotency

The National Institute of Health (NIH) Library of integrated network-based cellular signatures (LINCS) program is premised on the generation of a publicly available data resource of cell-based biochemical responses or "signatures" to genetic or environmental perturbations. NeuroLINCS uses human inducible pluripotent stem cells (hiPSCs), derived from patients and healthy controls, and differentiated into motor neuron cell cultures. This multi-laboratory effort strives to establish i) robust multi-omic workflows for hiPSC and differentiated neuronal cultures, ii) public annotated data sets and iii) relevant and targetable biological pathways of spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS). Here, we focus on the proteomics and the quality of the developed workflow of hiPSC lines from 6 individuals, though epigenomics and transcriptomics data are also publicly available. Known and commonly used markers representing 73 proteins were reproducibly quantified with consistent expression levels across all hiPSC lines. Data quality assessments, data levels and metadata of all 6 genetically diverse human iPSCs analysed by DIA-MS are parsable and available as a high-quality resource to the public.

Cellular Aging Secretes: a Comparison of Bone-Marrow-Derived and Induced Mesenchymal Stem Cells and Their Secretome Over Long-Term Culture

Mesenchymal stem cells (MSCs) hold promising therapeutic potential in several clinical applications, mainly due to their paracrine activity. The implementation of future secretome-based therapeutic strategies requires the use of easily accessible MSCs sources that provide high numbers of cells with homogenous characteristics. MSCs obtained from induced pluripotent stem cells (iMSCs) have been put forward as an advantageous alternative to the gold-standard tissue sources, such as bone marrow (BM-MSCs). In this study, we aimed at comparing the secretome of BM-MSCs and iMSCs over long-term culture. For that, we performed a broad characterization of both sources regarding their identity, proteomic secretome analysis, as well as replicative senescence and associated phenotypes, including its effects on MSCs secretome composition and immunomodulatory action. Our results evidence a rejuvenated phenotype of iMSCs, which is translated into a superior proliferative capacity before the induction of replicative senescence. Despite this significant difference between iMSCs and BM-MSCs proliferation, both untargeted and targeted proteomic analysis revealed a similar secretome composition for both sources in pre-senescent and senescent states. These results suggest that shifting from the use of BM-MSCs to a more advantageous source, like iMSCs, may yield similar therapeutic effects as identified over the past years for this gold-standard MSC source.

Dynamic Interactome of PRC2-EZH1 Complex Using Tandem-Affinity Purification and Quantitative Mass Spectrometry

The Polycomb repressive complex 2 (PRC2) is a well-characterized chromatin regulator of transcription programs acting through H3K27me3 deposition. In mammals, there are two main versions of PRC2 complexes: PRC2-EZH2, which is prevalent in cycling cells, and PRC2-EZH1 where EZH1 replaces EZH2 in post-mitotic tissues. Stoichiometry of PRC2 complex is dynamically modulated during cellular differentiation and various stress conditions. Therefore, unraveling unique architecture of PRC2 complexes under specific biological context through comprehensive and quantitative characterization could provide insight into the underlying mechanistic molecular mechanism in regulation of transcription process. In this chapter, we describe an efficient method which combines tandem-affinity purification (TAP) with label-free quantitative proteomics strategy for studying PRC2-EZH1 complex architecture alterations and identifying novel protein regulators in post-mitotic C2C12 skeletal muscle cells.

Proteomic profile of Candida albicans biofilm

Candida albicans biofilms are characterized by structural and cellular heterogeneity that confers antifungal resistance and immune evasion. Despite this, biofilm formation remains poorly understood. In this study, we used proteomic analysis to understand biofilm formation in C. albicans related to morphophysiological and architectural features. LC-MS/MS analysis revealed that 64 proteins were significantly modulated, of which 31 were upregulated and 33 were downregulated. The results indicate that metabolism (25 proteins), gene expression (13 proteins), stress response (7 proteins), and cell wall (5 proteins) composition are modulated. The rate of oxidative phosphorylation (OxPhos) and biosynthesis of UDP-N-acetylglucosamine, vitamin B6, and thiamine increased, while the rate of methionine biosynthesis decreased. There was a significant modification of the cell wall architecture due to higher levels of Sun41, Pir1 and Csh1 and increased glycosylation of proteins. It was observed that C. albicans induces hyphal growth by upregulating the expression of genes involved in cAMP-PKA and MAPK pathways. This study is significant in that it suggests an increase in OxPhos and alteration of cell wall architecture that could be contributing to the recalcitrance of C. albicans cells growing in biofilms. Nevertheless, a deeper investigation is needed to explore it further. SIGNIFICANCE: Candida sps is included in the list of pathogens with potential drug resistance threat due to the increased frequency especially colonization of medical devices, and tissues among the patients, in recent years. Significance of our study is that we are reporting traits like modulation in cell wall composition, amino acid and vitamin biosynthesis and importantly energy generation (OxPhos) etc. These traits could be conferring antifungal resistance, host immune evasion etc. and thus survival, in addition to facilitating biofilm formation. These findings are expected to prime the further studies on devising potent strategy against biofilm growth among the patients.

Secreted Amyloid Precursor Protein Alpha, a Neuroprotective Protein in the Brain Has Widespread Effects on the Transcriptome and Proteome of Human Inducible Pluripotent Stem Cell-Derived Glutamatergic Neurons Related to Memory Mechanisms

Secreted amyloid precursor protein alpha (sAPPα) processed from a parent human brain protein, APP, can modulate learning and memory. It has potential for development as a therapy preventing, delaying, or even reversing Alzheimer’s disease. In this study a comprehensive analysis to understand how it affects the transcriptome and proteome of the human neuron was undertaken. Human inducible pluripotent stem cell (iPSC)-derived glutamatergic neurons in culture were exposed to 1 nM sAPPα over a time course and changes in the transcriptome and proteome were identified with RNA sequencing and Sequential Window Acquisition of All THeoretical Fragment Ion Spectra-Mass Spectrometry (SWATH-MS), respectively. A large subset (∼30%) of differentially expressed transcripts and proteins were functionally involved with the molecular biology of learning and memory, consistent with reported links of sAPPα to memory enhancement, as well as neurogenic, neurotrophic, and neuroprotective phenotypes in previous studies. Differentially regulated proteins included those encoded in previously identified Alzheimer’s risk genes, APP processing related proteins, proteins involved in synaptogenesis, neurotransmitters, receptors, synaptic vesicle proteins, cytoskeletal proteins, proteins involved in protein and organelle trafficking, and proteins important for cell signalling, transcriptional splicing, and functions of the proteasome and lysosome. We have identified a complex set of genes affected by sAPPα, which may aid further investigation into the mechanism of how this neuroprotective protein affects memory formation and how it might be used as an Alzheimer’s disease therapy.

Prediction and Experimental Validation of a New Salinity-Responsive Cis-Regulatory Element (CRE) in a Tilapia Cell Line

Transcriptional regulation is a major mechanism by which organisms integrate gene x environment interactions. It can be achieved by coordinated interplay between cis-regulatory elements (CREs) and transcription factors (TFs). Euryhaline tilapia (Oreochromis mossambicus) tolerate a wide range of salinity and thus are an appropriate model to examine transcriptional regulatory mechanisms during salinity stress in fish. Quantitative proteomics in combination with the transcription inhibitor actinomycin D revealed 19 proteins that are transcriptionally upregulated by hyperosmolality in tilapia brain (OmB) cells. We searched the extended proximal promoter up to intron1 of each corresponding gene for common motifs using motif discovery tools. The top-ranked motif identified (STREME1) represents a binding site for the Forkhead box TF L1 (FoxL1). STREME1 function during hyperosmolality was experimentally validated by choosing two of the 19 genes, chloride intracellular channel 2 (clic2) and uridine phosphorylase 1 (upp1), that are enriched in STREME1 in their extended promoters. Transcriptional induction of these genes during hyperosmolality requires STREME1, as evidenced by motif mutagenesis. We conclude that STREME1 represents a new functional CRE that contributes to gene x environment interactions during salinity stress in tilapia. Moreover, our results indicate that FoxL1 family TFs are contribute to hyperosmotic induction of genes in euryhaline fish.

A Sensitive and Controlled Data-Independent Acquisition Method for Proteomic Analysis of Cell Therapies

Mass spectrometry (MS)-based proteomic measurements are uniquely poised to impact the development of cell and gene therapies. With the adoption of rigorous instrumental performance qualifications (PQs), large-scale proteomics can move from a research to a manufacturing control tool. Especially suited, data-independent acquisition (DIA) approaches have distinctive qualities to extend multiattribute method (MAM) principles to characterize the proteome of cell therapies. Here, we describe the development of a DIA method for the sensitive identification and quantification of proteins on a Q-TOF instrument. Using the improved acquisition parameters, we defined a control strategy and highlighted some metrics to improve the reproducibility of SWATH acquisition-based proteomic measurements. Finally, we applied the method to analyze the proteome of Jurkat cells that here serves as a model for human T-cells. Raw and processed data were deposited in PRIDE (PXD029780).

Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

The profound effects of and distress caused by the global COVID-19 pandemic highlighted what has been known in the health sciences a long time ago: that bacteria, fungi, viruses, and parasites continue to present a major threat to human health. Infectious diseases remain the leading cause of death worldwide, with antibiotic resistance increasing exponentially due to a lack of new treatments. In addition to this, many pathogens share the common trait of having the ability to modulate, and escape from, the host immune response. The challenge in medical microbiology is to develop and apply new experimental approaches that allow for the identification of both the microbe and its drug susceptibility profile in a time-sensitive manner, as well as to elucidate their molecular mechanisms of survival and immunomodulation. Over the last three decades, proteomics has contributed to a better understanding of the underlying molecular mechanisms responsible for microbial drug resistance and pathogenicity. Proteomics has gained new momentum as a result of recent advances in mass spectrometry. Indeed, mass spectrometry-based biomedical research has been made possible thanks to technological advances in instrumentation capability and the continuous improvement of sample processing and workflows. For example, high-throughput applications such as SWATH or Trapped ion mobility enable the identification of thousands of proteins in a matter of minutes. This type of rapid, in-depth analysis, combined with other advanced, supportive applications such as data processing and artificial intelligence, presents a unique opportunity to translate knowledge-based findings into measurable impacts like new antimicrobial biomarkers and drug targets. In relation to the Research Topic “Proteomic Approaches to Unravel Mechanisms of Resistance and Immune Evasion of Bacterial Pathogens,” this review specifically seeks to highlight the synergies between the powerful fields of modern proteomics and microbiology, as well as bridging translational opportunities from biomedical research to clinical practice.

14-3-3β is essential for milk composition stimulated by Leu/IGF-1 via IGF1R signaling pathway in BMECs

The cell proliferation of bovine mammary epithelial cells (BMECs) and consequent milk synthesis are regulated by multiple factors. The purpose of this study was to examine the effect of 14-3-3β on cellular proliferation and milk fat/β-casein synthesis in BMECs and reveal its underlying mechanisms. In this study, we employed gene function analysis to explore the regulatory effect and molecular mechanisms of 14-3-3β on milk synthesis and proliferation in BMECs. We found that leucine and IGF-1 enhance cell proliferation and milk synthesis in a 14-3-3β-dependent manner and only exhibiting such effect in the presence of 14-3-3β. We further determined that 14-3-3β interacts with the IGF1R self-phosphorylation site and it additionally mediated leucine and IGF-1 to stimulate the synthesis of milk through the IGF1R-AKT-mTORC1 signaling pathway. In summary, our data indicated that 14-3-3β mediates the expression of milk fat and protein stimulated by leucine and IGF-1, leading to lactogenesis through IGF1R signaling pathway in BMECs.

Proteome dataset of sea bass (Dicentrarchus labrax) skin-scales exposed to fluoxetine and estradiol

Contamination of aquatic ecosystems with anthropogenic pollutants, including pharmaceutical drugs, is a major concern worldwide. Aquatic organisms such as fish are particularly at risk of exposure to pollutants. The surface of fish is the first point of contact with pollutants, but few studies have considered the impact of pollutants on the skin-scale barrier. The present proteome data are the basis of the findings discussed in the associated research article “Proteomics of sea bass skin-scales exposed to the emerging pollutant fluoxetine compared to estradiol” [1]. Juvenile sea bass were exposed by intraperitoneal injections to: a) the antidepressant fluoxetine (FLX), a widely prescribed psychotropic drug and an emerging pollutant; b) the natural estrogen 17β-estradiol (E2) and c) the vehicle, coconut oil (control). The scale proteome of fish exposed to these compounds for 5 days was analysed using quantitative label-free proteomics technology SWATH-MS (sequential windowed data-independent acquisition of the total high-resolution-mass spectra). The proteome data generated was submitted to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD020983. LC-MS data from pooled protein extracts from the scales of all experimental groups was acquired using information-dependent acquisition (IDA) and 1,254 proteins were identified by searching against the sea bass genome database. 715 proteins were quantified by SWATH acquisition, and 213 proteins had modified levels (p < 0.05) between the E2- or FLX-exposed fish compared to the control. The main biological processes and KEGG pathways affected by E2 or FLX treatments were identified using Cytoscape/ClueGO enrichment analyses.

Spotted Fever Group Rickettsia Trigger Species-Specific Alterations in Macrophage Proteome Signatures with Different Impacts in Host Innate Inflammatory Responses

The molecular details underlying differences in pathogenicity between Rickettsia species remain to be fully understood. Evidence points to macrophage permissiveness as a key mechanism in rickettsial virulence. Different studies have shown that several rickettsial species responsible for mild forms of rickettsioses can also escape macrophage-mediated killing mechanisms and establish a replicative niche within these cells. However, their manipulative capacity with respect to host cellular processes is far from being understood. A deeper understanding of the interplay between mildly pathogenic rickettsiae and macrophages and the commonalities and specificities of host responses to infection would illuminate differences in immune evasion mechanisms and pathogenicity. We used quantitative proteomics by sequential windowed data independent acquisition of the total high-resolution mass spectra with tandem mass spectrometry (SWATH-MS/MS) to profile alterations resulting from infection of THP-1 macrophages with three mildly pathogenic rickettsiae: Rickettsia parkeri, Rickettsia africae, and Rickettsia massiliae, all successfully proliferating in these cells. We show that all three species trigger different proteome signatures. Our results reveal a significant impact of infection on proteins categorized as type I interferon responses, which here included several components of the retinoic acid-inducible gene I (RIG-1)-like signaling pathway, mRNA splicing, and protein translation. Moreover, significant differences in protein content between infection conditions provide evidence for species-specific induced alterations. Indeed, we confirm distinct impacts on host inflammatory responses between species during infection, demonstrating that these species trigger different levels of beta interferon (IFN-β), differences in the bioavailability of the proinflammatory cytokine interleukin 1β (IL-1β), and differences in triggering of pyroptotic events. This work reveals novel aspects and exciting nuances of macrophage-Rickettsia interactions, adding additional layers of complexity between Rickettsia and host cells' constant arms race for survival. IMPORTANCE The incidence of diseases caused by Rickettsia has been increasing over the years. It has long been known that rickettsioses comprise diseases with a continuous spectrum of severity. There are highly pathogenic species causing diseases that are life threatening if untreated, others causing mild forms of the disease, and a third group for which no pathogenicity to humans has been described. These marked differences likely reflect distinct capacities for manipulation of host cell processes, with macrophage permissiveness emerging as a key virulence trait. However, what defines pathogenicity attributes among rickettsial species is far from being resolved. We demonstrate that the mildly pathogenic Rickettsia parkeri, Rickettsia africae, and Rickettsia massiliae, all successfully proliferating in macrophages, trigger different proteome signatures in these cells and differentially impact critical components of innate immune responses by inducing different levels of beta interferon (IFN-β) and interleukin 1β (IL-1β) and different timing of pyroptotic events during infection. Our work reveals novel nuances in rickettsia-macrophage interactions, offering new clues to understand Rickettsia pathogenicity.

pH/Acetonitrile-Gradient Reversed-Phase Fractionation of Enriched Hyper-Citrullinated Library in Combination with LC-MS/MS Analysis for Confident Identification of Citrullinated Peptides

Citrullination, the Ca²⁺-driven enzymatic conversion of arginine residues to citrulline, is a posttranslational modification, implicated in several physiological and pathological processes. Several methods to detect citrullinated proteins have been developed, including color development reagent, fluorescence, phenylglyoxal, and antibody-based methods. These methods yet suffer from limitations in sensitivity, specificity, or citrullinated site determination. Mass spectrometry (MS)-based proteomic analysis has emerged as a promising method to resolve these problems. However, due to low abundance of citrullinated proteins and similar MS features to deamidation of asparagine and glutamine, confident identification of citrullinated proteome is challenging. Here, we present a systematic approach to identify a compendium of steps to enhance the number of detected citrullinated residue and implement diagnostic MS feature that allow the confidence of MS-based identifications. Our method is based on the concept of generation of hyper-citrullinated library with high-pH reversed-phase peptide fractionation that allows to enrich in low abundance citrullinated peptides and amplify the effect of charge loss upon citrullination. Application of our approach to complex global citrullino-proteome datasets demonstrates the confident assessment of citrullinated peptides, thereby enhancing the size and functional interpretation of citrullinated proteomes.

Quantitative proteomic analysis of hepatic tissue in allotetraploid hybridized from red crucian carp and common carp identified crucial proteins and pathways associated with metabolism and growth rate

Allotetraploid is a new species produced by distant hybridization between red crucian carp (Carassius auratus red var., abbreviated as RCC) and common carp (Cyprinus carpio L., abbreviated as CC). There is a significant difference in growth rate between allotetraploid and its parents. However, the underlying molecular mechanism is largely unknown. In this study, to find direct evidence associated with metabolism and growth rate in protein level, we performed quantitative proteomics analysis on liver tissues between allotetraploid and its parents. A total of 2502 unique proteins were identified and quantified by SWATH-MS in our proteomics profiling. Subsequently, comprehensive bioinformatics analyses including gene ontology enrichment analysis, pathway and network analysis, and protein-protein interaction analysis (PPI) were conducted based on differentially expressed proteins (DEPs) between allotetraploid and its parents. The results revealed several significant DEPs involved in metabolism pathways in liver. More specifically, the integrative analysis highlighted that the DEPs ACSBG1, OAT, and LDHBA play vital roles in metabolism pathways including "pentose phosphate pathway," "TCA cycle," and "glycolysis and gluconeogenesis." These could directly affect the growth rate in fresh water fishes by regulating the metabolism, utilization, and exchange of substance and energy. Since the liver is the central place for metabolism activity in animals, we firstly established the comprehensive and quantitative proteomics knowledge base for liver tissue from freshwater fishes, our study may serve as an irreplaceable reference for further studies regarding fishes' culture and growth.

CRB-SWATH: A Method for Enhancing Untargeted Precursor Ion Extraction and Automatically Constructing Their Tandem Mass Spectra from SWATH Datasets by Chromatographic Retention Behaviors

Sequential window acquisition of all theoretical spectra (SWATH) as a typical data-independent acquisition (DIA) strategy is favorable for untargeted metabolomics. It could theoretically acquire product ions of all precursor ions, including precursor ions showing chromatographic peaks of rather poor qualities. However, existing data processing methods present limited capabilities in capturing poor-quality peaks of precursor ions. Thus, although their product ions could be acquired, their precursor ions are absent. Here, we present a new strategy, chromatographic retention behavior-SWATH (CRB-SWATH), that could unbiasedly capture poor-quality peaks and provide high resolutions of multiplexed mass spectroscopy (MS/MS) spectra in SWATH datasets. CRB-SWATH monitors CRBs of SWATH-MS signals under a series of altered elution gradients. As signals of compounds differ from noise by showing CRBs, both the precursor and fragment ions are captured, while ignoring their peak qualities. Moreover, CRB-SWATH offers good chances to resolve highly multiplexed MS/MS spectra in SWATH datasets because precursor ions coeluted in a single elution gradient often present different CRBs. In the untargeted metabolic analysis of Hela cell extracts, CRB-SWATH showed the advantage in exclusively capturing 2645 ions of poor-quality peaks (i.e., tiny peaks, discontinuous ion traces, tailing peaks, zigzag peaks, etc.), accounting for 34.4% of all the untargeted precursor ions extracted. Therein, it is noteworthy that among 2116 negative ions detected in hydrophilic interaction liquid chromatography (HILIC) mode, 1284 poor-quality ion peaks (>60%) were exclusively captured by CRB-SWATH. As CRB-SWATH automatically captures a large sum of true ion peaks of poor qualities, extracts MS/MS spectra of high purities, and provides chromatographic retention behaviors of untargeted metabolites for identification and classification, it could be a useful metabolomics tool for understanding biological phenomena better.

Gene and protein expression in human megakaryocytes derived from induced pluripotent stem cells

BACKGROUND

There is interest in deriving megakaryocytes (MKs) from pluripotent stem cells (iPSC) for biological studies. We previously found that genomic structural integrity and genotype concordance is maintained in iPSC-derived MKs.

OBJECTIVE

To establish a comprehensive dataset of genes and proteins expressed in iPSC-derived MKs.

METHODS

iPSCs were reprogrammed from peripheral blood mononuclear cells (MNCs) and MKs were derived from the iPSCs in 194 healthy European American and African American subjects. mRNA was isolated and gene expression measured by RNA sequencing. Protein expression was measured in 62 of the subjects using mass spectrometry.

RESULTS AND CONCLUSIONS

MKs expressed genes and proteins known to be important in MK and platelet function and demonstrated good agreement with previous studies in human MKs derived from CD34+ progenitor cells. The percent of cells expressing the MK markers CD41 and CD42a was consistent in biological replicates, but variable across subjects, suggesting that unidentified subject-specific factors determine differentiation of MKs from iPSCs. Gene and protein sets important in platelet function were associated with increasing expression of CD41/42a, while those related to more basic cellular functions were associated with lower CD41/42a expression. There was differential gene expression by the sex and race (but not age) of the subject. Numerous genes and proteins were highly expressed in MKs but not known to play a role in MK or platelet function; these represent excellent candidates for future study of hematopoiesis, platelet formation, and/or platelet function.

The Isotopic Ac-IP Tag Enables Multiplexed Proteome Quantification in Data-Independent Acquisition Mode

Data-independent acquisition (DIA) is an increasingly used approach for quantitative proteomics. However, most current isotope labeling strategies are not suitable for DIA as they lead to more complex MS2 spectra or severe ratio distortion. As a result, DIA suffers from a lower throughput than data-dependent acquisition (DDA) due to a lower level of multiplexing. Herein, we synthesized an isotopically labeled acetyl-isoleucine-proline (Ac-IP) tag for multiplexed quantification in DIA. Differentially labeled peptides have distinct precursor ions carrying the quantitative information but identical MS2 spectra since the isotopically labeled Ac-Ile part leaves as a neutral loss upon collision-induced dissociation, while fragmentation of the peptide backbone generates regular fragment ions for identification. The Ac-IP-labeled samples can be analyzed using general DIA liquid chromatography–mass spectrometry settings, and the data obtained can be processed with established approaches. Relative quantification requires deconvolution of the isotope envelope of the respective precursor ions. Suitability of the Ac-IP tag is demonstrated with a triplex-labeled yeast proteome spiked with bovine serum albumin that was mixed at 10:5:1 ratios, resulting in measured ratios of 9.7:5.3:1.1.

Identification and Validation of Combination Plasma Biomarker of Afamin, Fibronectin and Sex Hormone-Binding Globulin to Predict Pre-eclampsia

The purpose of the present study was to identify a plasma protein biomarker able to predict pre-eclampsia (PE). Comprehensive quantitative proteomics using mass spectrometry with sequential window acquisition of all theoretical fragment ion spectra (SWATH-MS) was applied to plasma samples of 7 PE and 14 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE), and 11 proteins were selected as candidates potentially able to differentiate the two groups. Plasmas collected at gestational weeks 14-24 from 36 PE and 120 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE) were used to conduct selected reaction monitoring quantification analysis, optimize protein combinations and conduct internal validation, which consisted of 30 iterations of 10-fold cross-validation using multivariate logistic regression and receiver operating characteristic (ROC) analysis. The combination of afamin, fibronectin, and sex-hormone-binding globulin was selected as the best candidate. The 3-protein combination predictive model (predictive equation and cut-off value) generated using the internal validation subjects was successfully validated in another group of validation subjects (36 PE and 54 healthy (for PE subjects, plasma samples were taken before onset of PE)) and showed good predictive performance, with the area under the curve (AUC) 0.835 and odds ratio 13.43. In conclusion, we newly identified a 3-protein combination biomarker and established a predictive equation and cut-off value that can predict the onset of PE based on analysis of plasma samples collected during gestational weeks 14-24.

Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical Trials

TARGET (tumour characterisation to guide experimental targeted therapy) is a cancer precision medicine programme focused on molecular characterisation of patients entering early phase clinical trials. Performance status (PS) measures a patient's ability to perform a variety of activities. However, the quality of present algorithms to assess PS is limited and based on qualitative clinician assessment. Plasma samples from patients enrolled into TARGET were analysed using the mass spectrometry (MS) technique: sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. SWATH-MS was used on a discovery cohort of 55 patients to differentiate patients into either a good or poor prognosis by creation of a Wellness Score (WS) that showed stronger prediction of overall survival (p = 0.000551) compared to PS (p = 0.001). WS was then tested against a validation cohort of 77 patients showing significant (p = 0.000451) prediction of overall survival. WS in both sets had receiver operating characteristic curve area under the curve (AUC) values of 0.76 (p = 0.002) and 0.67 (p = 0.011): AUC of PS was 0.70 (p = 0.117) and 0.55 (p = 0.548). These signatures can now be evaluated further in larger patient populations to assess their utility in a clinical setting.

Proteogenomic Workflow Reveals Molecular Phenotypes Related to Breast Cancer Mammographic Appearance

Proteogenomic approaches have enabled the generat̲ion of novel information levels when compared to single omics studies although burdened by extensive experimental efforts. Here, we improved a data-independent acquisition mass spectrometry proteogenomic workflow to reveal distinct molecular features related to mammographic appearances in breast cancer. Our results reveal splicing processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Furthermore, we confirm previously detected enrichments of molecular pathways associated with estrogen receptor-dependent activity and provide novel evidence of epithelial-to-mesenchymal activity in mammography-detected spiculated tumors. Several transcript-protein pairs displayed radically different abundances depending on the overall clinical properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant tumor subgroups, which in turn alter both cancer biology and the abundance of biomarker candidates and drug targets.

Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis

Meningitis is a potentially life-threatening infection characterized by the inflammation of the leptomeningeal membranes. Many different viral and bacterial pathogens can cause meningitis, with differences in mortality rates, risk of developing neurological sequelae, and treatment options. Here, we constructed a compendium of digital cerebrospinal fluid (CSF) proteome maps to define pathogen-specific host response patterns in meningitis. The results revealed a drastic and pathogen-type specific influx of tissue-, cell-, and plasma proteins in the CSF, where, in particular, a large increase of neutrophil-derived proteins in the CSF correlated with acute bacterial meningitis. Additionally, both acute bacterial and viral meningitis result in marked reduction of brain-enriched proteins. Generation of a multiprotein LASSO regression model resulted in an 18-protein panel of cell- and tissue-associated proteins capable of classifying acute bacterial meningitis and viral meningitis. The same protein panel also enabled classification of tick-borne encephalitis, a subgroup of viral meningitis, with high sensitivity and specificity. The work provides insights into pathogen-specific host response patterns in CSF from different disease etiologies to support future classification of pathogen type based on host response patterns in meningitis.

Protein context shapes the specificity of SH3 domain-mediated interactions in vivo

Protein–protein interactions (PPIs) between modular binding domains and their target peptide motifs are thought to largely depend on the intrinsic binding specificities of the domains. The large family of SRC Homology 3 (SH3) domains contribute to cellular processes via their ability to support such PPIs. While the intrinsic binding specificities of SH3 domains have been studied in vitro, whether each domain is necessary and sufficient to define PPI specificity in vivo is largely unknown. Here, by combining deletion, mutation, swapping and shuffling of SH3 domains and measurements of their impact on protein interactions in yeast, we find that most SH3s do not dictate PPI specificity independently from their host protein in vivo. We show that the identity of the host protein and the position of the SH3 domains within their host are critical for PPI specificity, for cellular functions and for key biophysical processes such as phase separation. Our work demonstrates the importance of the interplay between a modular PPI domain such as SH3 and its host protein in establishing specificity to wire PPI networks. These findings will aid understanding how protein networks are rewired during evolution and in the context of mutation-driven diseases such as cancer.

The SRC Homology 3 (SH3) domains mediate protein–protein interactions (PPIs). Here, the authors assess the SH3-mediated PPIs in yeast, and show that the identity of the protein itself and the position of the SH3 both affect the interaction specificity and thus the PPI-dependent cellular functions.

Hypoxia and Hypoxia-Inducible Factor-1α Regulate Endoplasmic Reticulum Stress in Nucleus Pulposus Cells: Implications of Endoplasmic Reticulum Stress for Extracellular Matrix Secretion

Endoplasmic reticulum (ER) stress is shown to promote nucleus pulposus (NP) cell apoptosis and intervertebral disc degeneration. However, little is known about ER stress regulation by the hypoxic disc microenvironment and its contribution to extracellular matrix homeostasis. NP cells were cultured under hypoxia (1% partial pressure of oxygen) to assess ER stress status, and gain-of-function and loss-of-function approaches were used to assess the role of hypoxia-inducible factor (HIF)-1α in this pathway. In addition, the contribution of ER stress induction on the NP cell secretome was assessed by a nontargeted quantitative proteomic analysis by sequential windowed data independent acquisition of the total high-resolution mass spectra-mass spectrometry. NP cells exhibited a lower ER stress burden under hypoxia. Knockdown of HIF-1α increased C/EBP homologous protein, protein kinase RNA-like endoplasmic reticulum kinase (PERK), and activating transcription factor 6 (ATF6) levels, whereas HIF-1α stabilization decreased the expression of ER stress markers Ddit3, Hsp5a, Atf6, and Eif2a. Interestingly, ER stress inducers tunicamycin and thapsigargin induced HIF-1α activity under hypoxia while promoting the unfolded protein response. NP cell secretome analysis demonstrated an impact of ER stress induction on extracellular matrix secretion, with decreases in collagens and cell adhesion-related proteins. Moreover, analysis of transcriptomic data of NP tissues from aged mice and degenerated human discs showed higher levels of unfolded protein response markers and decreased levels of matrix components. Our study shows, for the first time, that hypoxia and HIF-1α attenuate ER stress responses in NP cells, and ER stress promotes inefficient extracellular matrix secretion under hypoxia.

Spatiotemporal profiling of cytosolic signaling complexes in living cells by selective proximity proteomics

Signaling complexes are often organized in a spatiotemporal manner and on a minute timescale. Proximity labeling based on engineered ascorbate peroxidase APEX2 pioneered in situ capture of spatiotemporal membrane protein complexes in living cells, but its application to cytosolic proteins remains limited due to the high labeling background. Here, we develop proximity labeling probes with increased labeling selectivity. These probes, in combination with label-free quantitative proteomics, allow exploring cytosolic protein assemblies such as phosphotyrosine-mediated protein complexes formed in response to minute-scale EGF stimulation. As proof-of-concept, we systematically profile the spatiotemporal interactome of the EGFR signaling component STS1. For STS1 core complexes, our proximity proteomics approach shows comparable performance to affinity purification-mass spectrometry-based temporal interactome profiling, while also capturing additional—especially endosomally-located—protein complexes. In summary, we provide a generic approach for exploring the interactome of mobile cytosolic proteins in living cells at a temporal resolution of minutes.

APEX-based proximity labeling allows capturing protein interaction dynamics but its high labeling background limits its utility for cytosolic proteins. Here, the authors develop more selective proximity labeling probes, enabling the APEX-based characterization of time-resolved cytosolic protein interactomes.

Virulence Biomarkers of Bursaphelenchus xylophilus: A Proteomic Approach

The pinewood nematode (PWN), Bursaphelenchus xylophilus, one of the most serious forest pests worldwide, is considered the causal agent of the pine wilt disease (PWD). The main host species belong to the genus Pinus, and a variation in the susceptibility of several pine species to PWN infection is well-known. It is also recognized that there is variation in the virulence among B. xylophilus isolates. In the present study, we applied a quantitative mass spectrometry-based proteomics approach to perform a deep characterization of proteomic changes across two B. xylophilus isolates with different virulence from different hosts and geographical origins. A total of 1,456 proteins were quantified and compared in the two isolates secretomes, and a total of 2,741 proteins were quantified and compared in the nematode proteomes in pine tree extract and fungus stimuli conditions. From the proteomic analyses, a group of proteins was selected and identified as potential virulence biomarkers and shed light on putative most pathogenic proteins of this plant-parasitic nematode. Proteomic data are available via ProteomeXchange with identifier PXD029377.

Mass spectrometry-based protein-protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.

Drinking water temperature affects cognitive function and progression of Alzheimer's disease in a mouse model

Lifestyle factors may affect mental health and play a critical role in the development of neurodegenerative diseases including Alzheimer's disease (AD). However, whether the temperatures of daily beverages have any impact on cognitive function and AD development has never been studied. In this study, we investigated the effects of daily drinking water temperatures on cognitive function and AD development and progression in mice and the underlying mechanisms. Cognitive function of mice was assessed using passive avoidance test, open field test, and Morris water maze. Wild-type Kunming mice receiving intragastric water (IW, 10 mL/kg, 2 times/day) at 0 °C for consecutive 15 days displayed significant cognitive defects accompanied by significant decrease in gain of body weight, gastric emptying rate, pepsin activity, and an increase in the energy charge in the cortex when compared with mice receiving the same amount of IW at 25 °C (a temperature mimicking most common drinking habits in human), suggesting the altered neuroenergetics may cause cognitive decline. Similarly, in the transgenic APPwse/PS1De9 familial AD mice and their age- and gender-matched wild-type C57BL/6 mice, receiving IW at 0 °C, but not at 25 °C, for 35 days caused a significant time-dependent decrease in body weight and cognitive function, accompanied by a decreased expression of PI3K, Akt, the glutamate/GABA ratio, as well as neuropathy with significant amyloid lesion in the cortex and hippocampus. All of these changes were significantly aggravated in the APPwse/PS1De9 mice than in the control C57BL/6 mice. These data demonstrate that daily beverage at 0 °C may alter brain insulin-mediated neuroenergetics, glutamate/GABA ratio, cause cognitive decline and neuropathy, and promote AD progression.

Comparative Analysis of Bursaphelenchus xylophilus Secretome Under Pinus pinaster and P. pinea Stimuli

The pinewood nematode (PWN), Bursaphelenchus xylophilus, the pine wilt disease's (PWD) causal agent, is a migratory endoparasitic nematode skilled to feed on pine tissues and on fungi that colonize the trees. In order to study B. xylophilus secretomes under the stimulus of pine species with different susceptibilities to disease, nematodes were exposed to aqueous pine extracts from Pinus pinaster (high-susceptible host) and P. pinea (low-susceptible host). Sequential windowed acquisition of all theoretical mass spectra (SWATH-MS) was used to determine relative changes in protein amounts between B. xylophilus secretions, and a total of 776 secreted proteins were quantified in both secretomes. From these, 22 proteins were found increased in the B. xylophilus secretome under the P. pinaster stimulus and 501 proteins increased under the P. pinea stimulus. Functional analyses of the 22 proteins found increased in the P. pinaster stimulus showed that proteins with peptidase, hydrolase, and antioxidant activities were the most represented. On the other hand, gene ontology (GO) enrichment analysis of the 501 proteins increased under the P. pinea stimulus revealed an enrichment of proteins with binding activity. The differences detected in the secretomes highlighted the diverse responses from the nematode to overcome host defenses with different susceptibilities and provide new clues on the mechanism behind the pathogenicity of this plant-parasitic nematode. Proteomic data are available via ProteomeXchange with identifier PXD024011.

SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles

Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state. A record of this paper's transparent peer review process is included in the Supplemental Information.

Mass spectrometry-based proteomics analyses of post-translational modifications and proteoforms in human pituitary adenomas

Pituitary adenoma (PA) is a common intracranial neoplasm, which affects the hypothalamus-pituitary-target organ axis systems, and is hazardous to human health. Post-translational modifications (PTMs), including phosphorylation, ubiquitination, nitration, and sumoylation, are vitally important in the PA pathogenesis. The large-scale analysis of PTMs could provide a global view of molecular mechanisms for PA. Proteoforms, which are used to define various protein structural and functional forms originated from the same gene, are the future direction of proteomics research. The global studies of different proteoforms and PTMs of hypophyseal hormones such as growth hormone (GH) and prolactin (PRL) and the proportion change of different GH proteoforms or PRL proteoforms in human pituitary tissue could provide new insights into the clinical value of pituitary hormones in PAs. Multiple quantitative proteomics methods, including mass spectrometry (MS)-based label-free and stable isotope-labeled strategies in combination with different PTM-peptide enrichment methods such as TiO₂ enrichment of tryptic phosphopeptides and antibody enrichment of other PTM-peptides increase the feasibility for researchers to study PA proteomes. This article reviews the research status of PTMs and proteoforms in PAs, including the enrichment method, technical limitation, quantitative proteomics strategies, and the future perspectives, to achieve the goals of in-depth understanding its molecular pathogenesis, and discovering effective biomarkers and clinical therapeutic targets for predictive, preventive, and personalized treatment of PA patients.

Revealing functional insights into ER proteostasis through proteomics and interactomics

The endoplasmic reticulum (ER), responsible for processing approximately one-third of the human proteome including most secreted and membrane proteins, plays a pivotal role in protein homeostasis (proteostasis). Dysregulation of ER proteostasis has been implicated in a number of disease states. As such, continued efforts are directed at elucidating mechanisms of ER protein quality control which are mediated by transient and dynamic protein-protein interactions with molecular chaperones, co-chaperones, protein folding and trafficking factors that take place in and around the ER. Technological advances in mass spectrometry have played a pivotal role in characterizing and understanding these protein-protein interactions that dictate protein quality control mechanisms. Here, we highlight the recent progress from mass spectrometry-based investigation of ER protein quality control in revealing the topological arrangement of the proteostasis network, stress response mechanisms that adjust the ER proteostasis capacity, and disease specific changes in proteostasis network engagement. We close by providing a brief outlook on underexplored areas of ER proteostasis where mass spectrometry is a tool uniquely primed to further expand our understanding of the regulation and coordination of protein quality control processes in diverse diseases.

A Versatile Isobaric Tag Enables Proteome Quantification in Data-Dependent and Data-Independent Acquisition Modes

Quantifying proteins based on peptide-coupled reporter ions is a multiplexed quantitative strategy in proteomics that alleviates the problem of ratio distortion caused by peptide cofragmentation, as commonly observed in other reporter-ion-based approaches, such as TMT and iTRAQ. Data-independent acquisition (DIA) is an attractive alternative to data-dependent acquisition (DDA) due to its better reproducibility. While multiplexed labeling is widely used in DDA, it is rarely used in DIA, presumably because current approaches lead to more complex MS2 spectra, severe ratio distortion, or to a reduction in quantification accuracy and precision. Herein, we present a versatile acetyl-alanine-glycine (Ac-AG) tag that conceals quantitative information in isobarically labeled peptides and reveals it upon tandem MS in the form of peptide-coupled reporter ions. Since the peptide-coupled reporter ion is precursor-specific while fragment ions of the peptide backbone originating from different labeling channels are identical, the Ac-AG tag is compatible with both DDA and DIA. By isolating the monoisotopic peak of the precursor ion in DDA, intensities of the peptide-coupled reporter ions represent the relative ratios between constituent samples, whereas in DIA, the ratio can be inferred after deconvoluting the peptide-coupled reporter ion isotopes. The proteome quantification capability of the Ac-AG tag was demonstrated by triplex labeling of a yeast proteome spiked with bovine serum albumin (BSA) over a 10-fold dynamic range. Within this complex proteomics background, BSA spiked at 1:5:10 ratios was detected at ratios of 1.00:4.87:10.13 in DDA and 1.16:5.20:9.64 in DIA.