The ProteomeXchange consortium at 10 years: 2023 update

SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution

The single-cell proteomics enables the direct quantification of protein abundance at the single-cell resolution, providing valuable insights into cellular phenotypes beyond what can be inferred from transcriptome analysis alone. However, insufficient large-scale integrated databases hinder researchers from accessing and exploring single-cell proteomics, impeding the advancement of this field. To fill this deficiency, we present a comprehensive database, namely Single-cell Proteomic DataBase (SPDB, https://scproteomicsdb.com/), for general single-cell proteomic data, including antibody-based or mass spectrometry-based single-cell proteomics. Equipped with standardized data process and a user-friendly web interface, SPDB provides unified data formats for convenient interaction with downstream analysis, and offers not only dataset-level but also protein-level data search and exploration capabilities. To enable detailed exhibition of single-cell proteomic data, SPDB also provides a module for visualizing data from the perspectives of cell metadata or protein features. The current version of SPDB encompasses 133 antibody-based single-cell proteomic datasets involving more than 300 million cells and over 800 marker/surface proteins, and 10 mass spectrometry-based single-cell proteomic datasets involving more than 4000 cells and over 7000 proteins. Overall, SPDB is envisioned to be explored as a useful resource that will facilitate the wider research communities by providing detailed insights into proteomics from the single-cell perspective.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

ALK signaling primes the DNA damage response sensitizing ALK-driven neuroblastoma to therapeutic ATR inhibition

High-risk neuroblastoma (NB) is a significant clinical challenge. MYCN and Anaplastic Lymphoma Kinase (ALK), which are often involved in high-risk NB, lead to increased replication stress in cancer cells, suggesting therapeutic strategies. We previously identified an ATR (ataxia telangiectasia and Rad3-related)/ALK inhibitor (ATRi/ALKi) combination as such a strategy in two independent genetically modified mouse NB models. Here, we identify an underlying molecular mechanism, in which ALK signaling leads to phosphorylation of ATR and CHK1, supporting an effective DNA damage response. The importance of ALK inhibition is supported by mouse data, in which ATRi monotreatment resulted in a robust initial response, but subsequent relapse, in contrast to a 14-d ALKi/ATRi combination treatment that resulted in a robust and sustained response. Finally, we show that the remarkable response to the 14-d combined ATR/ALK inhibition protocol reflects a robust differentiation response, reprogramming tumor cells to a neuronal/Schwann cell lineage identity. Our results identify an ability of ATR inhibition to promote NB differentiation and underscore the importance of further exploring combined ALK/ATR inhibition in NB, particularly in high-risk patient groups with oncogene-induced replication stress.

Illuminating phenotypic drug responses of sarcoma cells to kinase inhibitors by phosphoproteomics

Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect is particularly apparent in cancer entities such as sarcomas for which the oncogenic drivers are often not clear. To investigate more systematically how the cellular proteotypes of sarcoma cells shape their response to molecularly targeted drugs, we profiled the proteomes and phosphoproteomes of 17 sarcoma cell lines and screened the same against 150 cancer drugs. The resulting 2550 phenotypic profiles revealed distinct drug responses and the cellular activity landscapes derived from deep (phospho)proteomes (9-10,000 proteins and 10-27,000 phosphorylation sites per cell line) enabled several lines of analysis. For instance, connecting the (phospho)proteomic data with drug responses revealed known and novel mechanisms of action (MoAs) of KIs and identified markers of drug sensitivity or resistance. All data is publicly accessible via an interactive web application that enables exploration of this rich molecular resource for a better understanding of active signalling pathways in sarcoma cells, identifying treatment response predictors and revealing novel MoA of clinical KIs.

FAT10 is phosphorylated by IKKβ to inhibit the antiviral type-I interferon response

IFN-I secretion provides a rapid host defense against infection with RNA viruses. Within the host cell, viral RNA triggers the activation of the RIG-I signaling pathway, leading to the production of IFN-I. Because an exaggerated IFN-I response causes severe tissue damage, RIG-I signaling is tightly regulated. One of the factors that control the IFN-I response is the ubiquitin-like modifier FAT10, which is induced by TNF and IFNγ and targets covalently FAT10-linked proteins for proteasomal degradation. However, the mechanism of how FAT10 modulates IFN-I secretion remains to be fully elucidated. Here, we provide strong evidence that FAT10 is phosphorylated by IκB kinase β (IKKβ) upon TNF stimulation and during influenza A virus infection on several serine and threonine residues. FAT10 phosphorylation increases the binding of FAT10 to the TRAF3-deubiquitylase OTUB1 and its FAT10-mediated activation. Consequently, FAT10 phosphorylation results in a low ubiquitylation state of TRAF3, which is unable to maintain interferon regulatory factor 3 phosphorylation and downstream induction of IFN-I. Taken together, we reveal a mechanism of how phosphorylation of FAT10 limits the production of tissue-destructive IFN-I in inflammation.

Making MS Omics Data ML-Ready: SpeCollate Protocols

The increasing complexity and volume of mass spectrometry (MS) data have presented new challenges and opportunities for proteomics data analysis and interpretation. In this chapter, we provide a comprehensive guide to transforming MS data for machine learning (ML) training, inference, and applications. The chapter is organized into three parts. The first part describes the data analysis needed for MS-based experiments and a general introduction to our deep learning model SpeCollate-which we will use throughout the chapter for illustration. The second part of the chapter explores the transformation of MS data for inference, providing a step-by-step guide for users to deduce peptides from their MS data. This section aims to bridge the gap between data acquisition and practical applications by detailing the necessary steps for data preparation and interpretation. In the final part, we present a demonstrative example of SpeCollate, a deep learning-based peptide database search engine that overcomes the problems of simplistic simulation of theoretical spectra and heuristic scoring functions for peptide-spectrum matches by generating joint embeddings for spectra and peptides. SpeCollate is a user-friendly tool with an intuitive command-line interface to perform the search, showcasing the effectiveness of the techniques and methodologies discussed in the earlier sections and highlighting the potential of machine learning in the context of mass spectrometry data analysis. By offering a comprehensive overview of data transformation, inference, and ML model applications for mass spectrometry, this chapter aims to empower researchers and practitioners in leveraging the power of machine learning to unlock novel insights and drive innovation in the field of mass spectrometry-based omics.

Interactome Analysis Reveals a Link of the Novel ALMS1-CEP70 Complex to Centrosomal Clusters

Alström syndrome (ALMS) is a very rare autosomal-recessive disorder, causing a broad range of clinical defects most notably retinal degeneration, type 2 diabetes, and truncal obesity. The ALMS1 gene encodes a complex and huge ∼0.5 MDa protein, which has hampered analysis in the past. The ALMS1 protein is localized to the centrioles and the basal body of cilia and is involved in signaling processes, for example, TGF-β signaling. However, the exact molecular function of ALMS1 at the basal body remains elusive and controversial. We recently demonstrated that protein complex analysis utilizing endogenously tagged cells provides an excellent tool to investigate protein interactions of ciliary proteins. Here, CRISPR/Cas9-mediated endogenously tagged ALMS1 cells were used for affinity-based protein complex analysis. Centrosomal and microtubule-associated proteins were identified, which are potential regulators of ALMS1 function, such as the centrosomal protein 70 kDa (CEP70). Candidate proteins were further investigated in ALMS1-deficient hTERT-RPE1 cells. Loss of ALMS1 led to shortened cilia with no change in structural protein localization, for example, acetylated and ɣ-tubulin, Centrin-3, or the novel interactor CEP70. Conversely, reduction of CEP70 resulted in decreased ALMS1 at the ciliary basal body. Complex analysis of CEP70 revealed domain-specific ALMS1 interaction involving the TPR-containing C-terminal (TRP-CT) fragment of CEP70. In addition to ALMS1, several ciliary proteins, including CEP135, were found to specifically bind to the TPR-CT domain. Data are available via ProteomeXchange with the identifier PXD046401. Protein interactors identified in this study provide candidate lists that help to understand ALMS1 and CEP70 function in cilia-related protein modification, cell death, and disease-related mechanisms.

Transglutaminase 2 has higher affinity for relaxed than for stretched fibronectin fibers

Transglutaminase 2 (TG2) plays a vital role in stabilizing extracellular matrix (ECM) proteins through enzymatic crosslinking during tissue growth, repair, and inflammation. TG2 also binds non-covalently to fibronectin (FN), an essential component of the ECM, facilitating cell adhesion, migration, proliferation, and survival. However, the interaction between TG2 and fibrillar FN remains poorly understood, as most studies have focused on soluble or surface-adsorbed FN or FN fragments, which differ in their conformations from insoluble FN fibers. Using a well-established in vitro FN fiber stretch assay, we discovered that the binding of a crosslinking enzyme to ECM fibers is mechano-regulated. TG2 binding to FN is tuned by the mechanical tension of FN fibers, whereby TG2 predominantly co-localizes to low-tension FN fibers, while fiber stretching reduces their affinity for TG2. This mechano-regulated binding relies on the proximity between the N-terminal β-sandwich and C-terminal β-barrels of TG2. Crosslinking mass spectrometry (XL-MS) revealed a novel TG2-FN synergy site within TG2's C-terminal β-barrels that interacts with FN regions located outside of the canonical gelatin binding domain, specifically FNI2 and FNIII14-15. Combining XL-MS distance restraints with molecular docking revealed the mechano-regulated binding mechanism between TG2 and modules FNI7-9 by which mechanical forces regulate TG2-FN interactions. This highlights a previously unrecognized role of TG2 as a tension sensor for FN fibers. This novel interaction mechanism has significant implications in physiology and mechanobiology, including how forces regulate cell adhesion, spreading, migration, phenotype modulation, depending on the tensional state of ECM fibers. Data are available via ProteomeXchange with identifier PXD043976.

Liquid-chromatography mass spectrometry describes post-translational modification of Shewanella outer membrane proteins

Electrogenic bacteria deliver excess respiratory electrons to externally located metal oxide particles and electrodes. The biochemical basis for this process is arguably best understood for species of Shewanella where the integral membrane complex termed MtrCAB is key to electron transfer across the bacterial outer membranes. A crystal structure was recently resolved for MtrCAB from S. baltica OS185. However, X-ray diffraction did not resolve the N-terminal residues so that the lipidation status of proteins in the mature complex was poorly described. Here we report liquid chromatography mass spectrometry revealing the intact mass values for all three proteins in the MtrCAB complexes purified from Shewanella oneidensis MR-1 and S. baltica OS185. The masses of MtrA and MtrB are consistent with both proteins being processed by Signal Peptidase I and covalent attachment of ten c-type hemes to MtrA. The mass of MtrC is most reasonably interpreted as arising from protein processed by Signal Peptidase II to produce a diacylated lipoprotein containing ten c-type hemes. Our two-step protocol for liquid-chromatography mass spectrometry used a reverse phase column to achieve on-column detergent removal prior to gradient protein resolution and elution. We envisage the method will be capable of simultaneously resolving the intact mass values for multiple proteins in other membrane protein complexes.

eIF5A controls mitoprotein import by relieving ribosome stalling at the TIM50 translocase mRNA

The efficient import of nuclear-encoded proteins into mitochondria is crucial for proper mitochondrial function. The conserved translation factor eIF5A is primarily known as an elongation factor which binds ribosomes to alleviate ribosome stalling at sequences encoding polyprolines or combinations of proline with glycine and charged amino acids. eIF5A is known to impact the mitochondrial function across a variety of species although the precise molecular mechanism underlying this impact remains unclear. We found that depletion of eIF5A in yeast drives reduced translation and levels of TCA cycle and oxidative phosphorylation proteins. We further found that loss of eIF5A leads to the accumulation of mitoprotein precursors in the cytosol as well as to the induction of a mitochondrial import stress response. Here we identify an essential polyproline-containing protein as a direct eIF5A target for translation: the mitochondrial inner membrane protein Tim50, which is the receptor subunit of the TIM23 translocase complex. We show how eIF5A directly controls mitochondrial protein import through the alleviation of ribosome stalling along TIM50 mRNA at the mitochondrial surface. Removal of the polyprolines from Tim50 rescues the mitochondrial import stress response, as well as the translation of oxidative phosphorylation reporter genes in an eIF5A loss of function. Overall, our findings elucidate how eIF5A impacts the mitochondrial function by reducing ribosome stalling and facilitating protein translation, thereby positively impacting the mitochondrial import process.

The function of ER-phagy receptors is regulated through phosphorylation-dependent ubiquitination pathways

Selective autophagy of the endoplasmic reticulum (ER), known as ER-phagy, is an important regulator of ER remodeling and essential to maintain cellular homeostasis during environmental changes. We recently showed that members of the FAM134 family play a critical role during stress-induced ER-phagy. However, the mechanisms on how they are activated remain largely unknown. In this study, we analyze phosphorylation of FAM134 as a trigger of FAM134-driven ER-phagy upon mTOR (mechanistic target of rapamycin) inhibition. An unbiased screen of kinase inhibitors reveals CK2 to be essential for FAM134B- and FAM134C-driven ER-phagy after mTOR inhibition. Furthermore, we provide evidence that ER-phagy receptors are regulated by ubiquitination events and that treatment with E1 inhibitor suppresses Torin1-induced ER-phagy flux. Using super-resolution microscopy, we show that CK2 activity is essential for the formation of high-density FAM134B and FAM134C clusters. In addition, dense clustering of FAM134B and FAM134C requires phosphorylation-dependent ubiquitination of FAM134B and FAM134C. Treatment with the CK2 inhibitor SGC-CK2-1 or mutation of FAM134B and FAM134C phosphosites prevents ubiquitination of FAM134 proteins, formation of high-density clusters, as well as Torin1-induced ER-phagy flux. Therefore, we propose that CK2-dependent phosphorylation of ER-phagy receptors precedes ubiquitin-dependent activation of ER-phagy flux.

Interactions of Histone Deacetylase 6 with DNA Damage Repair Factors Strengthen its Utility as a Combination Drug Target in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is the deadliest gynecologic malignancy in women. The low survival rate is largely due to drug resistance. Approximately 80% of patients who initially respond to treatment relapse and become drug-resistant. The lack of effective second-line therapeutics remains a substantial challenge for BRCA-1/2 wild-type HGSOC patients. Histone Deacetylases (HDACs) are promising targets in HGSOC treatment; however, the mechanism and efficacy of HDAC inhibitors are understudied in HGSOC. In order to consider HDACs as a treatment target, an improved understanding of their function within HGSOC is required. This includes elucidating HDAC6-specific protein-protein interactions. In this study, we carried out substrate trapping followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) to elucidate HDAC6 catalytic domain (CD)-specific interactors in the context of BRCA-1/2 wild-type HGSOC. Overall, this study identified new HDAC6 substrates that may be unique to HGSOC. The HDAC6-CD1 mutant condition contained the largest number of significant proteins compared to the CD2 mutant and the CD1/2 mutant conditions, suggesting the HDAC6-CD1 domain has catalytic activity that is independent of CD2. Among the identified substrates were proteins involved in DNA damage repair including PARP proteins. These findings further justify the use of HDAC inhibitors as a combination treatment with platinum chemotherapy agents and PARP inhibitors in HGSOC.

Phytocystatin 6 is a context-dependent, tight-binding inhibitor of Arabidopsis thaliana legumain isoform β

Plant legumains are crucial for processing seed storage proteins and are critical regulators of plant programmed cell death. Although research on legumains boosted recently, little is known about their activity regulation. In our study, we used pull-down experiments to identify AtCYT6 as a natural inhibitor of legumain isoform β (AtLEGβ) in Arabidopsis thaliana. Biochemical analysis revealed that AtCYT6 inhibits both AtLEGβ and papain-like cysteine proteases through two separate cystatin domains. The N-terminal domain inhibits papain-like proteases, while the C-terminal domain inhibits AtLEGβ. Furthermore, we showed that AtCYT6 interacts with legumain in a substrate-like manner, facilitated by a conserved asparagine residue in its reactive center loop. Complex formation was additionally stabilized by charged exosite interactions, contributing to pH-dependent inhibition. Processing of AtCYT6 by AtLEGβ suggests a context-specific regulatory mechanism with implications for plant physiology, development, and programmed cell death. These findings enhance our understanding of AtLEGβ regulation and its broader physiological significance.

DPP9 Stabilizes NRF2 to Suppress Ferroptosis and Induce Sorafenib Resistance in Clear Cell Renal Cell Carcinoma

The KEAP1-NRF2 axis is the principal regulator of cellular responses to oxidative and electrophilic stressors. NRF2 hyperactivation is frequently observed in many types of cancer and promotes cancer initiation, progression, metastasis, and resistance to various therapies. Here, we determined that dipeptidyl peptidase 9 (DPP9) is a regulator of the KEAP1-NRF2 pathway in clear cell renal cell carcinoma (ccRCC). DPP9 was markedly overexpressed at the mRNA and protein levels in ccRCC, and high DPP9 expression levels correlated with advanced tumor stage and poor prognosis in patients with ccRCC. Protein affinity purification to identify functional partners of DPP9 revealed that it bound to KEAP1 via a conserved ESGE motif. DPP9 disrupted KEAP1-NRF2 binding by competing with NRF2 for binding to KEAP1 in an enzyme-independent manner. Upregulation of DPP9 led to stabilization of NRF2, driving NRF2-dependent transcription and thereby decreasing cellular reactive oxygen species levels. Moreover, DPP9 overexpression suppressed ferroptosis and induced resistance to sorafenib in ccRCC cells, which was largely dependent on the NRF2 transcriptional target SLC7A11. Collectively, these findings indicate that the accumulation of DPP9 results in hyperactivation of the NRF2 pathway to promote tumorigenesis and intrinsic drug resistance in ccRCC.

SIGNIFICANCE

DPP9 overcomes oxidative stress and suppresses ferroptosis in ccRCC by binding to KEAP1 and promoting NRF2 stability, which drives tumor development and sorafenib resistance.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry (MS) experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here, we leveraged recent advances in ribosome profiling and MS to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly expressed to be detected by shotgun MS at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for 4 noncanonical proteins in MS data, which were also supported by evolution and translation data. These results illustrate the power of MS to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly expressed proteins.

Naringenin improves muscle endurance via activation of the Sp1-ERRγ transcriptional axis

Skeletal muscle function declines in the aging process or disease; however, until now, skeletal muscle has remained one of the organs most undertreated with medication. In this study, naringenin (NAR) was found to build muscle endurance in wild-type mice of different ages by increasing oxidative myofiber numbers and aerobic metabolism, and it ameliorates muscle dysfunction in mdx mice. The transcription factor Sp1 was identified as a direct target of NAR and was shown to mediate the function of NAR on muscle. Moreover, the binding site of NAR on Sp1 was further validated as GLN-110. NAR enhances the binding of Sp1 to the CCCTGCCCTC sequence of the Esrrg promoter by promoting Sp1 phosphorylation, thus upregulating Esrrg expression. The identification of the Sp1-ERRγ transcriptional axis is of great significance in basic muscle research, and this function of NAR has potential implications for the improvement of muscle function and the prevention of muscle atrophy.

Autophagy-mediated control of ribosome homeostasis in oncogene-induced senescence

Oncogene-induced senescence (OIS) is a persistent anti-proliferative response that acts as a barrier against malignant transformation. During OIS, cells undergo dynamic remodeling, which involves alterations in protein and organelle homeostasis through autophagy. Here, we show that ribosomes are selectively targeted for degradation by autophagy during OIS. By characterizing senescence-dependent alterations in the ribosomal interactome, we find that the deubiquitinase USP10 dissociates from the ribosome during the transition to OIS. This release of USP10 leads to an enhanced ribosome ubiquitination, particularly of small subunit proteins, including lysine 275 on RPS2. Both reinforcement of the USP10-ribosome interaction and mutation of RPS2 K275 abrogate ribosomal delivery to lysosomes without affecting bulk autophagy. We show that the selective recruitment of ubiquitinated ribosomes to autophagosomes is mediated by the p62 receptor. While ribophagy is not required for the establishment of senescence per se, it contributes to senescence-related metabolome alterations and facilitates the senescence-associated secretory phenotype.

A stationary phase with a positively charged surface allows for minimizing formic acid concentration in the mobile phase, enhancing electrospray ionization in LC-MS proteomic experiments

The default choice of mobile phase acidifier for bottom-up LC-MS proteomic analyses is 0.10% formic acid because of its decent acidity, decent ion pairing ability, and low suppression of electrospray ionization. In recent years, state-of-the-art columns have been designed specifically to provide efficient separation even when using an MS-friendly mobile phase of low ionic strength. Despite this, no attempts have been made to improve the sensitivity of the MS-based analytical methods by reducing the amount of formic acid in the mobile phase. In this study, we evaluated the effect of reduced formic acid concentration in the mobile phase on the chromatographic behavior and MS response of peptides when separated using columns packed with a C18 stationary phase with a positively charged surface. Using 0.01% formic acid in the mobile phase maintained excellent chromatographic performance and increased MS signal response compared to the standard of 0.10%. The enhanced MS response translated to about 50% improved peptide identifications depending on the complexity and amount of sample injected. The increased retention of peptides at a reduced formic acid concentration was directly proportional to the number of acidic residues in the peptide sequence. The study was carried out by covering a spectrum of protein samples with varied complexity using analytical flow, micro-, and nanoflow regimes to expand the applicability in routine practice.

Proteomic analysis reveals changes in the proteome of human THP-1 macrophages infected with Paracoccidioides brasiliensis

Paracoccidioides spp. is the etiologic agent of Paracoccidioidomycosis (PCM), a systemic disease with wide distribution in Latin America. Macrophages are very important cells during the response to infection by P. brasiliensis. In this study, we performed a proteomic analysis to evaluate the consequences of P. brasiliensis yeast cells on the human THP-1 macrophage proteome. We have identified 443 and 2247 upregulated or downregulated proteins, respectively, in macrophages co-cultured with yeast cells of P. brasiliensis in comparison to control macrophages unexposed to the fungus. Proteomic analysis revealed that interaction with P. brasiliensis caused metabolic changes in macrophages that drastically affected energy production pathways. In addition, these macrophages presented regulated many factors related to epigenetic modifications and gene transcription as well as a decrease of many proteins associated to the immune system activity. This is the first human macrophage proteome derived from interactions with P. brasiliensis, which contributes to elucidating the changes that occur during the host response to this fungus. Furthermore, it highlights proteins that may be targets for the development of new therapeutic approaches to PCM.

The twin-arginine translocation system is vital for cell adhesion and uptake of iron in the cystic fibrosis pathogen Achromobacter xylosoxidans

BACKGROUND

Achromobacter xylosoxidans is an emerging pathogen that causes airway infections in patients with cystic fibrosis. Knowledge of virulence factors and protein secretion systems in this bacterium is limited. Twin arginine translocation (Tat) is a protein secretion system that transports folded proteins across the inner cell membranes of gram-negative bacteria. Tat has been shown to be important for virulence and cellular processes in many different bacterial species. This study aimed to investigate the role of Tat in iron metabolism and host cell adhesion in A. xylosoxidans.

METHODS

Putative Tat substrates in A. xylosoxidans were identified using the TatFind, TatP, and PRED-Tat prediction tools. An isogenic tatC deletion mutant (ΔtatC) was generated and phenotypically characterized. The wild-type and ΔtatC A. xylosoxidans were fractionated into cytosolic, membrane, and periplasmic fractions, and the expressed proteome of the different fractions was analyzed using liquid chromatography-mass spectrometry (LC-MS/MS).

RESULTS

A total of 128 putative Tat substrates were identified in the A. xylosoxidans proteome. The ΔtatC mutant showed attenuated host cell adhesion, growth rate, and iron acquisition. Twenty predicted Tat substrates were identified as expressed proteins in the periplasmic compartment, nine of which were associated with the wild type.

CONCLUSION

The data indicate that Tat secretion is important for iron acquisition and host cell adhesion in A. xylosoxidans.

Engineered immunomodulatory extracellular vesicles derived from epithelial cells acquire capacity for positive and negative T cell co-stimulation in cancer and autoimmunity

Extracellular vesicles (EVs) are generated by all cells and systemic administration of allogenic EVs derived from epithelial and mesenchymal cells have been shown to be safe, despite carrying an array of functional molecules, including thousands of proteins. To address whether epithelial cells derived EVs can be modified to acquire the capacity to induce immune response, we engineered 293T EVs to harbor the immunomodulatory CD80, OX40L and PD-L1 molecules. We demonstrated abundant levels of these proteins on the engineered cells and EVs. Functionally, the engineered EVs efficiently elicit positive and negative co-stimulation in human and murine T cells. In the setting of cancer and auto-immune hepatitis, the engineered EVs modulate T cell functions and alter disease progression. Moreover, OX40L EVs provide additional benefit to anti-CTLA-4 treatment in melanoma-bearing mice. Our work provides evidence that epithelial cell derived EVs can be engineered to induce immune responses with translational potential to modulate T cell functions in distinct pathological settings.

The intracellular helical bundle of human glucose transporter GLUT4 is important for complex formation with ASPL

Glucose transporters (GLUTs) are responsible for transporting hexose molecules across cellular membranes. In adipocytes, insulin stimulates glucose uptake by redistributing GLUT4 to the plasma membrane. In unstimulated adipose-like mouse cell lines, GLUT4 is known to be retained intracellularly by binding to TUG protein, while upon insulin stimulation, GLUT4 dissociates from TUG. Here, we report that the TUG homolog in human, ASPL, exerts similar properties, i.e., forms a complex with GLUT4. We describe the structural details of complex formation by combining biochemical assays with cross-linking mass spectrometry and computational modeling. Combined, the data suggest that the intracellular domain of GLUT4 binds to the helical lariat of ASPL and contributes to the regulation of GLUT4 trafficking by cooperative binding.

IdeS, a secreted proteinase of Streptococcus pyogenes, is bound to a nuclease at the bacterial surface where it inactivates opsonizing IgG antibodies

The important bacterial pathogen Streptococcus pyogenes secretes IdeS (immunoglobulin G-degrading enzyme of S. pyogenes), a proteinase that cleaves human immunoglobulin G (IgG) antibodies in the hinge region resulting in Fc (fragment crystallizable) and F(ab')2 (fragment antigen-binding) fragments and protects the bacteria against phagocytic killing. Experiments with radiolabeled IdeS and flow cytometry demonstrated that IdeS binds to the surface of S. pyogenes, and the interaction was most prominent in conditions resembling those in the pharynx (acidic pH and low salt), the habitat for S. pyogenes. SpnA (S. pyogenes nuclease A) is a cell wall-anchored DNase. A dose-dependent interaction between purified SpnA and IdeS was demonstrated in slot binding and surface plasmon resonance spectroscopy experiments. Gel filtration showed that IdeS forms proteolytically active complexes with SpnA in solution, and super-resolution fluorescence microscopy revealed the presence of SpnA-IdeS complexes at the surface of S. pyogenes. Finally, specific IgG antibodies binding to S. pyogenes surface antigens were efficiently cleaved by surface-associated IdeS. IdeS is secreted by all S. pyogenes isolates and cleaves IgG antibodies with a unique degree of specificity and efficiency. These properties and the finding here that the proteinase is present and fully active at the bacterial surface in complex with SpnA implicate an important role for IdeS in S. pyogenes biology and pathogenesis.

Genomic disturbance of vitellogenin 2 (vtg2) leads to vitellin membrane deficiencies and significant mortalities at early stages of embryonic development in zebrafish (Danio rerio)

The specific functions and essentiality of type II vitellogenin (Vtg2) in early zebrafish development were investigated in this study. A vtg2-mutant zebrafish line was produced and effects of genomic disturbance were observed in F2 females and F3 offspring. No change in vtg2 transcript has been detected, however, Vtg2 abundance in F2 female liver was 5×, and in 1 hpf F3 vtg2-mutant embryos was 3.8× less than Wt (p < 0.05). Fecundity was unaffected while fertilization rate was more than halved in F2 vtg2-mutant females (p < 0.05). Hatching rate was significantly higher in F3 vtg2-mutant embryos in comparison to Wt embryos. Survival rate declined drastically to 29% and 18% at 24 hpf and 20 dpf, respectively, in F3 vtg2-mutant embryos. The introduced mutation caused vitelline membrane deficiencies, significant mortalities at early embryonic stages, and morphological abnormalities in the surviving F3 vtg2-mutant larvae. Overrepresentation of histones, zona pellucida proteins, lectins, and protein degradation related proteins in F3 vtg2-mutant embryos provide evidence to impaired mechanisms involved in vitellin membrane formation. Overall findings imply a potential function of Vtg2 in acquisition of vitellin membrane integrity, among other reproductive functions, and therefore, its essentiality in early zebrafish embryo development.

Proteomics and bioinformatics investigations to improve serological diagnosis of canine brucellosis

PURPOSE

Brucella canis is pathogenic for dogs and humans. Serological diagnosis is a cost-effective approach for disease surveillance, but a major drawback of current serological tests is the cross-reactivity with other bacteria that results in false positive reactions. Development of indirect tests with improved sensitivity and specificity that use selected B. canis proteins instead of the whole antigen remain a priority.

EXPERIMENTAL DESIGN

A western blotting assay was developed to define the serum antibody patterns associated to infection using a panel of positive and negative dog sera. B. canis positive sera recognized immunogenic bands ranging from 7 to 30 kDa that were then submitted to ESI-LC-MS/MS and analyzed by bioinformatics tools.

RESULTS

A total of 398 B. canis proteins were identified. Bioinformatics tools identified 16 non cytoplasmic immunogenic proteins predicted as non-homologous with the most important Brucella cross-reactive bacteria and nine B. canis proteins non-homologous to B. ovis; among the latter, one resulted non-homologous to B. melitensis. Data are available via ProteomeXchange with identifier PXD042682.

CONCLUSIONS AND CLINICAL RELEVANCE

The western blotting test developed was able to distinguish between infected and non-infected animals and may serve as a confirmatory test for the serological diagnosis of B. canis. The mass spectrometry and in silico results lead to the identification of specific candidate antigens that pave the way for the development of more accurate indirect diagnostic tests.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

From multi-omics approaches to personalized medicine in myocardial infarction

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.

A Bioconductor workflow for processing, evaluating, and interpreting expression proteomics data

Background: Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods: Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilizes open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results: The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions: A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

Data-Independent Acquisition Mass Spectrometry Analysis of FFPE Rectal Cancer Samples Offers In-Depth Proteomics Characterization of the Response to Neoadjuvant Chemoradiotherapy

Locally advanced rectal cancer (LARC) presents a challenge in identifying molecular markers linked to the response to neoadjuvant chemoradiotherapy (nCRT). This study aimed to utilize a sensitive proteomic method, data-independent mass spectrometry (DIA-MS), to extensively analyze the LARC proteome, seeking individuals with favorable initial responses suitable for a watch-and-wait approach. This research addresses the unmet need to understand the response to treatment, potentially guiding personalized strategies for LARC patients. Post-treatment assessment included MRI scans and proctoscopy. This research involved 97 LARC patients treated with intense chemoradiotherapy, comprising radiation and chemotherapy. Out of 97 LARC included in this study, we selected 20 samples with the most different responses to nCRT for proteome profiling (responders vs. non-responders). This proteomic approach shows extensive proteome coverage in LARC samples. The analysis identified a significant number of proteins compared to a prior study. A total of 915 proteins exhibited differential expression between the two groups, with certain signaling pathways associated with response mechanisms, while top candidates had good predictive potential. Proteins encoded by genes SMPDL3A, PCTP, LGMN, SYNJ2, NHLRC3, GLB1, and RAB43 showed high predictive potential of unfavorable treatment outcome, while RPA2, SARNP, PCBP2, SF3B2, HNRNPF, RBBP4, MAGOHB, DUT, ERG28, and BUB3 were good predictive biomarkers of favorable treatment outcome. The identified proteins and related biological processes provide promising insights that could enhance the management and care of LARC patients.

Genetic deficiency of ribosomal rescue factor HBS1L causes retinal dystrophy associated with Pelota and EDF1 depletion

Inherited retinal diseases (IRDs) encompass a genetically diverse group of conditions in which mutations in genes critical to retinal function lead to progressive loss of photoreceptor cells and subsequent visual impairment. A handful of ribosome-associated genes have been implicated in retinal disorders alongside neurological phenotypes. This study focuses on the HBS1L gene, encoding HBS1 Like Translational GTPase which has been recognized as a critical ribosomal rescue factor. Previously, we have reported a female child carrying biallelic HBS1L mutations, manifesting growth restriction, developmental delay, and hypotonia. In this study, we describe her ophthalmologic findings, compare them with the Hbs1ltm1a/tm1a hypomorph mouse model, and evaluate the underlying microscopic and molecular perturbations. The patient was noted to have impaired visual function observed by electroretinogram (ERG), with dampened amplitudes of a- and b-waves in both rod- and cone-mediated responses. Hbs1ltm1a/tm1a mice exhibited profound retinal thinning of the entire retina, specifically of the outer retinal photoreceptor layer, detected using in vivo imaging of optical coherence tomography (OCT) and retinal cross sections. TUNEL assay revealed retinal degeneration due to extensive photoreceptor cell apoptosis. Loss of HBS1L resulted in comprehensive proteomic alterations in mass spectrometry analysis, with169 proteins increased and 480 proteins decreased including many critical IRD-related proteins. GO biological process and GSEA analyses reveal that these downregulated proteins are primarily involved in photoreceptor cell development, cilium assembly, phototransduction, and aerobic respiration. Furthermore, apart from the diminished level of PELO, a known partner protein, HBS1L depletion was accompanied by reduction in translation machinery associated 7 homolog (Tma7), and Endothelial differentiation-related factor 1(Edf1) proteins, the latter of which coordinates cellular responses to ribosome collisions. This novel connection between HBS1L and ribosome collision sensor (EDF1) further highlights the intricate mechanisms underpinning ribosomal rescue and quality control that are essential to maintain homeostasis of key proteins of retinal health, such as rhodopsin.

Cardiomyocyte precursors generated by direct reprogramming and molecular beacon selection attenuate ventricular remodeling after experimental myocardial infarction

BACKGROUND

Direct cardiac reprogramming is currently being investigated for the generation of cells with a true cardiomyocyte (CM) phenotype. Based on the original approach of cardiac transcription factor-induced reprogramming of fibroblasts into CM-like cells, various modifications of that strategy have been developed. However, they uniformly suffer from poor reprogramming efficacy and a lack of translational tools for target cell expansion and purification. Therefore, our group has developed a unique approach to generate proliferative cells with a pre-CM phenotype that can be expanded in vitro to yield substantial cell doses.

METHODS

Cardiac fibroblasts were reprogrammed toward CM fate using lentiviral transduction of cardiac transcriptions factors (GATA4, MEF2C, TBX5, and MYOCD). The resulting cellular phenotype was analyzed by RNA sequencing and immunocytology. Live target cells were purified based on intracellular CM marker expression using molecular beacon technology and fluorescence-activated cell sorting. CM commitment was assessed using 5-azacytidine-based differentiation assays and the therapeutic effect was evaluated in a mouse model of acute myocardial infarction using echocardiography and histology. The cellular secretome was analyzed using mass spectrometry.

RESULTS

We found that proliferative CM precursor-like cells were part of the phenotype spectrum arising during direct reprogramming of fibroblasts toward CMs. These induced CM precursors (iCMPs) expressed CPC- and CM-specific proteins and were selectable via hairpin-shaped oligonucleotide hybridization probes targeting Myh6/7-mRNA-expressing cells. After purification, iCMPs were capable of extensive expansion, with preserved phenotype when under ascorbic acid supplementation, and gave rise to CM-like cells with organized sarcomeres in differentiation assays. When transplanted into infarcted mouse hearts, iCMPs prevented CM loss, attenuated fibrotic scarring, and preserved ventricular function, which can in part be attributed to their substantial secretion of factors with documented beneficial effect on cardiac repair.

CONCLUSIONS

Fibroblast reprogramming combined with molecular beacon-based cell selection yields an iCMP-like cell population with cardioprotective potential. Further studies are needed to elucidate mechanism-of-action and translational potential.

Spectroscape enables real-time query and visualization of a spectral archive in proteomics

In proteomics, spectral archives organize the enormous amounts of publicly available peptide tandem mass spectra by similarity, offering opportunities for error correction and novel discoveries. Here we adapt an indexing algorithm developed by Facebook for organizing online multimedia resources to tandem mass spectra and achieve practically instantaneous retrieval and clustering of approximate nearest neighbors in a large spectral archive. An interactive web-based graphical user interface enables the user to view a query spectrum in its clustered neighborhood, which facilitates contextual validation of peptide identifications and exploration of the dark proteome.

Mapping the castor bean endosperm proteome revealed a metabolic interaction between plastid, mitochondria, and peroxisomes to optimize seedling growth

In this work, we studied castor-oil plant Ricinus communis as a classical system for endosperm reserve breakdown. The seeds of castor beans consist of a centrally located embryo with the two thin cotyledons surrounded by the endosperm. The endosperm functions as major storage tissue and is packed with nutritional reserves, such as oil, proteins, and starch. Upon germination, mobilization of the storage reserves requires inter-organellar interplay of plastids, mitochondria, and peroxisomes to optimize growth for the developing seedling. To understand their metabolic interactions, we performed a large-scale organellar proteomic study on castor bean endosperm. Organelles from endosperm of etiolated seedlings were isolated and subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS). Computer-assisted deconvolution algorithms were applied to reliably assign the identified proteins to their correct subcellular localization and to determine the abundance of the different organelles in the heterogeneous protein samples. The data obtained were used to build a comprehensive metabolic model for plastids, mitochondria, and peroxisomes during storage reserve mobilization in castor bean endosperm.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

The Golgi stacking protein GRASP55 is targeted by the natural compound prodigiosin

BACKGROUND

The bacterial secondary metabolite prodigiosin has been shown to exert anticancer, antimalarial, antibacterial and immunomodulatory properties. With regard to cancer, it has been reported to affect cancer cells but not non-malignant cells, rendering prodigiosin a promising lead compound for anticancer drug discovery. However, a direct protein target has not yet been experimentally identified.

METHODS

We used mass spectrometry-based thermal proteome profiling in order to identify target proteins of prodigiosin. For target validation, we employed a genetic knockout approach and electron microscopy.

RESULTS

We identified the Golgi stacking protein GRASP55 as target protein of prodigiosin. We show that prodigiosin treatment severely affects Golgi morphology and functionality, and that prodigiosin-dependent cytotoxicity is partially reduced in GRASP55 knockout cells. We also found that prodigiosin treatment results in decreased cathepsin activity and overall blocks autophagic flux, whereas co-localization of the autophagosomal marker LC3 and the lysosomal marker LAMP1 is clearly promoted. Finally, we observed that autophagosomes accumulate at GRASP55-positive structures, pointing towards an involvement of an altered Golgi function in the autophagy-inhibitory effect of this natural compound.

CONCLUSION

Taken together, we propose that prodigiosin affects autophagy and Golgi apparatus integrity in an interlinked mode of action involving the regulation of organelle alkalization and the Golgi stacking protein GRASP55. Video Abstract.

Combination of transcriptomic, proteomic, and degradomic profiling reveals common and distinct patterns of pathogen-induced cell death in maize

Regulated cell death (RCD) is crucial for plant development, as well as in decision-making in plant-microbe interactions. Previous studies revealed components of the molecular network controlling RCD, including different proteases. However, the identity, the proteolytic network as well as molecular components involved in the initiation and execution of distinct plant RCD processes, still remain largely elusive. In this study, we analyzed the transcriptome, proteome, and N-terminome of Zea mays leaves treated with the Xanthomonas effector avrRxo1, the mycotoxin Fumonisin B1 (FB1), or the phytohormone salicylic acid (SA) to dissect plant cellular processes related to cell death and plant immunity. We found highly distinct and time-dependent biological processes being activated on transcriptional and proteome levels in response to avrRxo1, FB1, and SA. Correlation analysis of the transcriptome and proteome identified general, as well as trigger-specific markers for cell death in Zea mays. We found that proteases, particularly papain-like cysteine proteases, are specifically regulated during RCD. Collectively, this study characterizes distinct RCD responses in Z. mays and provides a framework for the mechanistic exploration of components involved in the initiation and execution of cell death.

Loss of the parkinsonism-associated protein FBXO7 in glutamatergic forebrain neurons in mice leads to abnormal motor behavior and synaptic defects

Mutations in PARK15, which encodes for the F-box protein FBXO7 have been associated with Parkinsonian Pyramidal syndrome, a rare and complex movement disorder with Parkinsonian symptoms, pyramidal tract signs and juvenile onset. Our previous study showed that systemic loss of Fbxo7 in mice causes motor defects and premature death. We have also demonstrated that FBXO7 has a crucial role in neurons as the specific deletion in tyrosine hydroxylase-positive or glutamatergic forebrain neurons leads to late-onset or early-onset motor dysfunction, respectively. In this study, we examined NEX-Cre;Fbxo7fl/fl mice, in which Fbxo7 was specifically deleted in glutamatergic projection neurons. The effects of FBXO7 deficiency on striatal integrity were investigated with HPLC and histological analyses. NEX-Cre;Fbxo7fl/fl mice revealed an increase in striatal dopamine concentrations, changes in the glutamatergic, GABAergic and dopaminergic pathways, astrogliosis and microgliosis and little or no neuronal loss in the striatum. To determine the effects on the integrity of the synapse, we purified synaptic membranes, subjected them to quantitative mass spectrometry analysis and found alterations in the complement system, endocytosis and exocytosis pathways. These neuropathological changes coincide with alterations in spontaneous home cage behavior. Taken together, our findings suggest that FBXO7 is crucial for corticostriatal projections and the synaptic integrity of the striatum, and consequently for proper motor control.

The functional and structural characterization of Xanthomonas campestris pv. campestris core effector XopP revealed a new kinase activity

Exo70B1 is a protein subunit of the exocyst complex with a crucial role in a variety of cell mechanisms, including immune responses against pathogens. The calcium-dependent kinase 5 (CPK5) of Arabidopsis thaliana (hereafter Arabidopsis), phosphorylates AtExo70B1 upon functional disruption. We previously reported that, the Xanthomonas campestris pv. campestris effector XopP compromises AtExo70B1, while bypassing the host's hypersensitive response, in a way that is still unclear. Herein we designed an experimental approach, which includes biophysical, biochemical, and molecular assays and is based on structural and functional predictions, utilizing AplhaFold and DALI online servers, respectively, in order to characterize the in vivo XccXopP function. The interaction between AtExo70B1 and XccXopP was found very stable in high temperatures, while AtExo70B1 appeared to be phosphorylated at XccXopP-expressing transgenic Arabidopsis. XccXopP revealed similarities with known mammalian kinases and phosphorylated AtExo70B1 at Ser107, Ser111, Ser248, Thr309, and Thr364. Moreover, XccXopP protected AtExo70B1 from AtCPK5 phosphorylation. Together these findings show that XccXopP is an effector, which not only functions as a novel serine/threonine kinase upon its host target AtExo70B1 but also protects the latter from the innate AtCPK5 phosphorylation, in order to bypass the host's immune responses. Data are available via ProteomeXchange with the identifier PXD041405.

Tenofovir Activation is Diminished in the Brain and Liver of Creatine Kinase Brain-Type Knockout Mice

Tenofovir (TFV) is a nucleotide reverse transcriptase inhibitor prescribed for the treatment and prevention of human immunodeficiency virus infection, and the treatment of chronic hepatitis B virus infection. Here, we demonstrate that creatine kinase brain-type (CKB) can form tenofovir-diphosphate (TFV-DP), the pharmacologically active metabolite, in vitro, and identify nine missense mutations (C74S, R96P, S128R, R132H, R172P, R236Q, C283S, R292Q, and H296R) that diminish this activity. Additional characterization of these mutations reveal that five (R96P, R132H, R236Q, C283S, and R292Q) have ATP dephosphorylation catalytic efficiencies less than 20% of wild-type (WT), and seven (C74S, R96P, R132H, R172P, R236Q, C283S, and H296P) induce thermal instabilities. To determine the extent CKB contributes to TFV activation in vivo, we generated a CKB knockout mouse strain, Ckbtm1Nnb. Using an in vitro assay, we show that brain lysates of Ckbtm1Nnb male and female mice form 70.5% and 77.4% less TFV-DP than wild-type brain lysates of the same sex, respectively. Additionally, we observe that Ckbtm1Nnb male mice treated with tenofovir disoproxil fumarate for 14 days exhibit a 22.8% reduction in TFV activation in liver compared to wild-type male mice. Lastly, we utilize mass spectrometry-based proteomics to elucidate the impact of the knockout on the abundance of nucleotide and small molecule kinases in the brain and liver, adding to our understanding of how loss of CKB may be impacting tenofovir activation in these tissues. Together, our data suggest that disruptions in CKB may lower levels of active drug in brain and liver.

Hyodeoxycholic acid ameliorates nonalcoholic fatty liver disease by inhibiting RAN-mediated PPARα nucleus-cytoplasm shuttling

Nonalcoholic fatty liver disease (NAFLD) is usually characterized with disrupted bile acid (BA) homeostasis. However, the exact role of certain BA in NAFLD is poorly understood. Here we show levels of serum hyodeoxycholic acid (HDCA) decrease in both NAFLD patients and mice, as well as in liver and intestinal contents of NAFLD mice compared to their healthy counterparts. Serum HDCA is also inversely correlated with NAFLD severity. Dietary HDCA supplementation ameliorates diet-induced NAFLD in male wild type mice by activating fatty acid oxidation in hepatic peroxisome proliferator-activated receptor α (PPARα)-dependent way because the anti-NAFLD effect of HDCA is abolished in hepatocyte-specific Pparα knockout mice. Mechanistically, HDCA facilitates nuclear localization of PPARα by directly interacting with RAN protein. This interaction disrupts the formation of RAN/CRM1/PPARα nucleus-cytoplasm shuttling heterotrimer. Our results demonstrate the therapeutic potential of HDCA for NAFLD and provide new insights of BAs on regulating fatty acid metabolism.

Column storage enables edge computation of biological big data on 5G networks

With the continuous improvement of biological detection technology, the scale of biological data is also increasing, which overloads the central-computing server. The use of edge computing in 5G networks can provide higher processing performance for large biological data analysis, reduce bandwidth consumption and improve data security. Appropriate data compression and reading strategy becomes the key technology to implement edge computing. We introduce the column storage strategy into mass spectrum data so that part of the analysis scenario can be completed by edge computing. Data produced by mass spectrometry is a typical biological big data based. A blood sample analysed by mass spectrometry can produce a 10 gigabytes digital file. By introducing the column storage strategy and combining the related prior knowledge of mass spectrometry, the structure of the mass spectrum data is reorganized, and the result file is effectively compressed. Data can be processed immediately near the scientific instrument, reducing the bandwidth requirements and the pressure of the central server. Here, we present Aird-Slice, a mass spectrum data format using the column storage strategy. Aird-Slice reduces volume by 48% compared to vendor files and speeds up the critical computational step of ion chromatography extraction by an average of 116 times over the test dataset. Aird-Slice provides the ability to analyze biological data using an edge computing architecture on 5G networks.

Interpreting biologically informed neural networks for enhanced proteomic biomarker discovery and pathway analysis

The incorporation of machine learning methods into proteomics workflows improves the identification of disease-relevant biomarkers and biological pathways. However, machine learning models, such as deep neural networks, typically suffer from lack of interpretability. Here, we present a deep learning approach to combine biological pathway analysis and biomarker identification to increase the interpretability of proteomics experiments. Our approach integrates a priori knowledge of the relationships between proteins and biological pathways and biological processes into sparse neural networks to create biologically informed neural networks. We employ these networks to differentiate between clinical subphenotypes of septic acute kidney injury and COVID-19, as well as acute respiratory distress syndrome of different aetiologies. To gain biological insight into the complex syndromes, we utilize feature attribution-methods to introspect the networks for the identification of proteins and pathways important for distinguishing between subtypes. The algorithms are implemented in a freely available open source Python-package ( https://github.com/InfectionMedicineProteomics/BINN ).

Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis

Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Integrated proteomics and metabolomics analysis revealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our integrated analysis provides a multidimensional understanding of SA-AKI and identifies potential pathways for this condition.

Ccr4-Not ubiquitin ligase signaling regulates ribosomal protein homeostasis and inhibits 40S ribosomal autophagy

The Ccr4-Not complex containing the Not4 ubiquitin ligase regulates gene transcription and mRNA decay, yet it also has poorly defined roles in translation, proteostasis, and endolysosomal-dependent nutrient signaling. To define how Ccr4-Not mediated ubiquitin signaling regulates these additional processes, we performed quantitative proteomics in the yeast Saccharomyces cerevisiae lacking the Not4 ubiquitin ligase, and also in cells overexpressing either wild-type or functionally inactive ligase. Herein, we provide evidence that both increased and decreased Ccr4-Not ubiquitin signaling disrupts ribosomal protein (RP) homeostasis independently of reduced RP mRNA changes or reductions in known Not4 ribosomal substrates. Surprisingly, we also find that both Not4-mediated ubiquitin signaling, and the Ccr4 subunit, actively inhibit 40S ribosomal autophagy. This 40S autophagy is independent of canonical Atg7-dependent macroautophagy, thus indicating microautophagy activation is responsible. Furthermore, the Not4 ligase genetically interacts with endolysosomal pathway effectors to control both RP expression and 40S autophagy efficiency. Overall, we demonstrate that balanced Ccr4-Not ligase activity maintains RP homeostasis, and that Ccr4-Not ubiquitin signaling interacts with the endolysosomal pathway to both regulate RP expression and inhibit 40S ribosomal autophagy.

Combination of HBA1, TTR, and SERPINF2 in plasma defines phenotype correlated with severe burn outcome

Recent advancements in proteomics allow for the concurrent identification and quantification of multiple proteins. This study aimed to identify proteins associated with severe burn pathology and establish a clinically useful molecular pathology classification. In a retrospective observational study, blood samples were collected from severe burn patients. Proteins were measured using mass spectrometry, and prognosis-related proteins were extracted by comparing survivors and non-survivors. Enrichment and ROC analyses evaluated the extracted proteins, followed by latent class analysis. Measurements were performed on 83 burn patients. In the non-survivor group, ten proteins significantly changing on the day of injury were associated with metabolic processes and toxin responses. ROC analysis identified HBA1, TTR, and SERPINF2 with AUCs > 0.8 as predictors of 28-day mortality. Latent class analysis classified three molecular pathotypes, and plasma mass spectrometry revealed ten proteins associated with severe burn prognosis. Molecular pathotypes based on HBA1, TTR, and SERPINF2 significantly correlated with outcomes.

Platelet-derived exerkine CXCL4/platelet factor 4 rejuvenates hippocampal neurogenesis and restores cognitive function in aged mice

The beneficial effects of physical activity on brain ageing are well recognised, with exerkines, factors that are secreted into the circulation in response to exercise, emerging as likely mediators of this response. However, the source and identity of these exerkines remain unclear. Here we provide evidence that an anti-geronic exerkine is secreted by platelets. We show that platelets are activated by exercise and are required for the exercise-induced increase in hippocampal precursor cell proliferation in aged mice. We also demonstrate that increasing the systemic levels of the platelet-derived exerkine CXCL4/platelet factor 4 (PF4) ameliorates age-related regenerative and cognitive impairments in a hippocampal neurogenesis-dependent manner. Together these findings highlight the role of platelets in mediating the rejuvenating effects of exercise during physiological brain ageing.

Perinatal iron restriction is associated with changes in neonatal cardiac function and structure in a sex-dependent manner

Iron deficiency (ID) is common during gestation and in early infancy and can alter developmental trajectories with lasting consequences on cardiovascular health. While the effects of ID and anemia on the mature heart are well documented, comparatively little is known about their effects and mechanisms on offspring cardiac development and function in the neonatal period. Female Sprague-Dawley rats were fed an iron-restricted or iron-replete diet before and during pregnancy. Cardiac function was assessed in a cohort of offspring on postnatal days (PD) 4, 14, and 28 by echocardiography; a separate cohort was euthanized for tissue collection and hearts underwent quantitative shotgun proteomic analysis. ID reduced body weight and increased relative heart weights at all time points assessed, despite recovering from anemia by PD28. Echocardiographic studies revealed unique functional impairments in ID male and female offspring, characterized by greater systolic dysfunction in the former and greater diastolic dysfunction in the latter. Proteomic analysis revealed down-regulation of structural components by ID, as well as enriched cellular responses to stress; in general, these effects were more pronounced in males. ID causes functional changes in the neonatal heart, which may reflect an inadequate or maladaptive compensation to anemia. This identifies systolic and diastolic dysfunction as comorbidities to perinatal ID anemia which may have important implications for both the short- and long-term cardiac health of newborn babies. Furthermore, therapies which improve cardiac output may mitigate the effects of ID on organ development.

Identification of Potential Bioactive Peptides in Sheep Milk Kefir through Peptidomic Analysis at Different Fermentation Times

Sheep farming is an important socioeconomic activity in most Mediterranean countries, particularly Spain, where it contributes added value to rural areas. Sheep milk is used in Spain mainly for making cheese, but it can be used also for making other dairy products, such as the lactic-alcoholic fermentation product known as kefir. Dairy products have health benefits because, among other reasons, they contain molecules with biological activity. In this work, we performed a proteomics strategy to identify the peptidome, i.e., the set of peptides contained in sheep milk kefir fermented for four different periods of time, aiming to understand changes in the pattern of digestion of milk proteins, as well as to identify potential bioactive peptides. In total, we identified 1942 peptides coming from 11 different proteins, and found that the unique peptides differed qualitatively among samples and their numbers increased along the fermentation time. These changes were supported by the increase in ethanol, lactic acid, and D-galactose concentrations, as well as proteolytic activity, as the fermentation progressed. By searching in databases, we found that 78 of the identified peptides, all belonging to caseins, had potential biological activity. Of these, 62 were not previously found in any milk kefir from other animal species. This is the first peptidomic study of sheep milk kefir comprising time-course comparison.