Integrated proteomics reveals autophagy landscape and an autophagy receptor controlling PKA-RI complex homeostasis in neurons.

Autophagy is a conserved, catabolic process essential for maintaining cellular homeostasis. Malfunctional autophagy contributes to neurodevelopmental and neurodegenerative diseases. However, the exact role and targets of autophagy in human neurons remain elusive. Here we report a systematic investigation of neuronal autophagy targets through integrated proteomics. Deep proteomic profiling of multiple autophagy-deficient lines of human induced neurons, mouse brains, and brain LC3-interactome reveals roles of neuronal autophagy in targeting proteins of multiple cellular organelles/pathways, including endoplasmic reticulum (ER), mitochondria, endosome, Golgi apparatus, synaptic vesicle (SV) for degradation. By combining phosphoproteomics and functional analysis in human and mouse neurons, we uncovered a function of neuronal autophagy in controlling cAMP-PKA and c-FOS-mediated neuronal activity through selective degradation of the protein kinase A - cAMP-binding regulatory (R)-subunit I (PKA-RI) complex. Lack of AKAP11 causes accumulation of the PKA-RI complex in the soma and neurites, demonstrating a constant clearance of PKA-RI complex through AKAP11-mediated degradation in neurons. Our study thus reveals the landscape of autophagy degradation in human neurons and identifies a physiological function of autophagy in controlling homeostasis of PKA-RI complex and specific PKA activity in neurons.

Longitudinal markers of cerebral amyloid angiopathy and related inflammation in rTg-DI rats.

Cerebral amyloid angiopathy (CAA) is a prevalent vascular dementia and common comorbidity of Alzheimer's disease (AD). While it is known that vascular fibrillar amyloid ß (Aß) deposits leads to vascular deterioration and can drive parenchymal CAA related inflammation (CAA-ri), underlying mechanisms of CAA pathology remain poorly understood. Here, we conducted brain regional proteomic analysis of early and late disease stages in the rTg-DI CAA rat model to gain molecular insight to mechanisms of CAA/CAA-ri progression and identify potential brain protein markers of CAA/CAA-ri. Longitudinal brain regional proteomic analysis revealed increased differentially expressed proteins (DEP) including ANXA3, HTRA1, APOE, CST3, and CLU, shared between the cortex, hippocampus, and thalamus, at both stages of disease in rTg-DI rats. Subsequent pathway analysis indicated pathway enrichment and predicted activation of TGF-ß1, which was confirmed by immunolabeling and ELISA. Further, we identified numerous CAA related DEPs associate with astrocytes (HSPB1 and MLC1) and microglia (ANXA3, SPARC, TGF-ß1) not previously associated with astrocytes or microglia in other AD models, possibly indicating that they are specific to CAA-ri. Thus, the data presented here identify several potential brain protein biomarkers of CAA/CAA-ri while providing novel molecular and mechanistic insight to mechanisms of CAA and CAA-ri pathological progression and glial cell mediated responses.

An integrated toolkit for human microglia functional genomics.

BACKGROUND: Microglia, the brain's resident immune cells, play vital roles in brain development, and disorders like Alzheimer's disease (AD). Human iPSC-derived microglia (iMG) provide a promising model to study these processes. However, existing iMG generation protocols face challenges, such as prolonged differentiation time, lack of detailed characterization, and limited gene function investigation via CRISPR-Cas9. METHODS: Our integrated toolkit for in-vitro microglia functional genomics optimizes iPSC differentiation into iMG through a streamlined two-step, 20-day process, producing iMG with a normal karyotype. We confirmed the iMG's authenticity and quality through single-cell RNA sequencing, chromatin accessibility profiles (ATAC-Seq), proteomics and functional tests. The toolkit also incorporates a drug-dependent CRISPR-ON/OFF system for temporally controlled gene expression. Further, we facilitate the use of multi-omic data by providing online searchable platform that compares new iMG profiles to human primary microglia: https://sherlab.shinyapps.io/IPSC-derived-Microglia/ . RESULTS: Our method generates iMG that closely align with human primary microglia in terms of transcriptomic, proteomic, and chromatin accessibility profiles. Functionally, these iMG exhibit Ca2 + transients, cytokine driven migration, immune responses to inflammatory signals, and active phagocytosis of CNS related substrates including synaptosomes, amyloid beta and myelin. Significantly, the toolkit facilitates repeated iMG harvesting, essential for large-scale experiments like CRISPR-Cas9 screens. The standalone ATAC-Seq profiles of our iMG closely resemble primary microglia, positioning them as ideal tools to study AD-associated single nucleotide variants (SNV) especially in the genome regulatory regions. CONCLUSIONS: Our advanced two-step protocol rapidly and efficiently produces authentic iMG. With features like the CRISPR-ON/OFF system and a comprehensive multi-omic data platform, our toolkit equips researchers for robust microglial functional genomic studies. By facilitating detailed SNV investigation and offering a sustainable cell harvest mechanism, the toolkit heralds significant progress in neurodegenerative disease drug research and therapeutic advancement.

The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling.

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

Two-Dimensional Gel Electrophoresis for Protein Separation of Plant Samples.

This chapter provides a description of the procedure for two-dimensional electrophoresis that can be performed for any given gel size and isoelectric focusing range. This will enable the operator to recognize critical steps and gain sufficient information to generate 2D images suitable for computer-assisted analysis of 2D-gel, as well as mass spectrometry analysis for protein identification and characterization.

One-Dimensional Acrylamide Gel Electrophoresis for Analysis of Plant Samples.

Polyacrylamide gel electrophoresis (PAGE) is a widely used technique for separating proteins from complex plant samples. Prior to the analysis, proteins must be extracted from plant tissues, which are rather complex than other types of biological material. Different protocols have been applied depending on the protein source, such as seeds, pollen, leaves, roots, and flowers. Total protein amounts must also be determined before conducting gel electrophoresis. The most common methodologies include PAGE under native or denaturing conditions. Both procedures are used consequently for protein identification and characterization via mass spectrometry. Additionally, various staining procedures are available to visualize protein bands in the gel, facilitating the software-based digital evaluation of the gel through image acquisition.

Sample Preparation and Phosphopeptide Enrichment for Plant Phosphoproteomics via Label-Free Mass Spectrometry.

Phosphopeptide enrichment is the main bottleneck of every phosphorylation study. Therefore, in this chapter, a general workflow tries to overbridge the hurdles of plant sample handling from sample collection to protein extraction, protein solubilization, enzymatic digestion, and enrichment step prior to mass spectrometry. The workflow provides information to perform global proteomics as well as phosphoproteomics enabling the researcher to use the protocol in both fields.

Droplet-based proteomics reveals CD36 as a marker for progenitors in mammary basal epithelium.

Deep proteomic profiling of rare cell populations has been constrained by sample input requirements. Here, we present DROPPS (droplet-based one-pot preparation for proteomic samples), an accessible low-input platform that generates high-fidelity proteomic profiles of 100-2,500 cells. By applying DROPPS within the mammary epithelium, we elucidated the connection between mitochondrial activity and clonogenicity, identifying CD36 as a marker of progenitor capacity in the basal cell compartment. We anticipate that DROPPS will accelerate biology-driven proteomic research for a multitude of rare cell populations.

Gingival proteomics reveals the role of TGF beta and YAP/TAZ signaling in Raine syndrome fibrosis.

Raine syndrome (RNS) is a rare autosomal recessive osteosclerotic dysplasia. RNS is caused by loss-of-function disease-causative variants of the FAM20C gene that encodes a kinase that phosphorylates most of the secreted proteins found in the body fluids and extracellular matrix. The most common RNS clinical features are generalized osteosclerosis, facial dysmorphism, intracerebral calcifications and respiratory defects. In non-lethal RNS forms, oral traits include a well-studied hypoplastic amelogenesis imperfecta (AI) and a much less characterized gingival phenotype. We used immunomorphological, biochemical, and siRNA approaches to analyze gingival tissues and primary cultures of gingival fibroblasts of two unrelated, previously reported RNS patients. We showed that fibrosis, pathological gingival calcifications and increased expression of various profibrotic and pro-osteogenic proteins such as POSTN, SPARC and VIM were common findings. Proteomic analysis of differentially expressed proteins demonstrated that proteins involved in extracellular matrix (ECM) regulation and related to the TGFß/SMAD signaling pathway were increased. Functional analyses confirmed the upregulation of TGFß/SMAD signaling and subsequently uncovered the involvement of two closely related transcription cofactors important in fibrogenesis, Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ). Knocking down of FAM20C confirmed the TGFß-YAP/TAZ interplay indicating that a profibrotic loop enabled gingival fibrosis in RNS patients. In summary, our in vivo and in vitro data provide a detailed description of the RNS gingival phenotype. They show that gingival fibrosis and calcifications are associated with, and most likely caused by excessed ECM production and disorganization. They furthermore uncover the contribution of increased TGFß-YAP/TAZ signaling in the pathogenesis of the gingival fibrosis.

CHMP5 attenuates osteoarthritis via inhibiting chondrocyte apoptosis and extracellular matrix degradation: involvement of NF-κB pathway.

BACKGROUND: Osteoarthritis (OA), the most common joint disease, is linked with chondrocyte apoptosis and extracellular matrix (ECM) degradation. Charged multivesicular body protein 5 (CHMP5), a member of the multivesicular body, has been reported to serve as an anti-apoptotic protein to participate in leukemia development. However, the effects of CHMP5 on apoptosis and ECM degradation in OA remain unclear. METHODS: In this study, quantitative proteomics was performed to analyze differential proteins between normal and OA patient articular cartilages. The OA mouse model was constructed by the destabilization of the medial meniscus (DMM). In vitro, interleukin-1 beta (IL-1ß) was used to induce OA in human chondrocytes. CHMP5 overexpression and silencing vectors were created using an adenovirus system. The effects of CHMP5 on IL-1ß-induced chondrocyte apoptosis were investigated by CCK-8, flow cytometry, and western blot. The effects on ECM degradation were examined by western blot and immunofluorescence. The potential mechanism was explored by western blot and Co-IP assays. RESULTS: Downregulated CHMP5 was identified by proteomics in OA patient cartilages, which was verified in human and mouse articular cartilages. CHMP5 overexpression repressed cell apoptosis and ECM degradation in OA chondrocytes. However, silencing CHMP5 exacerbated OA chondrocyte apoptosis and ECM degradation. Furthermore, we found that the protective effect of CHMP5 against OA was involved in nuclear factor kappa B (NF-κB) signaling pathway. CONCLUSIONS: This study demonstrated that CHMP5 repressed IL-1ß-induced chondrocyte apoptosis and ECM degradation and blocked NF-κB activation. It was shown that CHMP5 might be a novel potential therapeutic target for OA in the future.

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

Optimizing environmental enrichment for Sprague Dawley rats: Exemplary insights into the liver proteome.

BACKGROUND: Considering the expected increase in the elderly population and the growing emphasis on aging-related biomedical research, the demand for aged laboratory animals has surged, challenging established husbandry practices. Our objective was to establish a cost-effective method for environmental enrichment, utilizing the liver as a representative organ to assess potential metabolic changes in response to differing enrichment levels. METHODS: We conducted a six-month study involving 24 male Sprague Dawley rats, randomly assigned to four environmental enrichment groups. Two groups were housed in standard cages, while the others were placed in modified rabbit cages. Half of the groups received weekly playtime in an activity focused rat housing unit. We evaluated hormone levels, playtime behavior, and subjective handling experience. Additionally, liver tissue proteomic analysis was performed. RESULTS: Initial corticosterone levels and those after 3 and 6 months showed no significant differences. Yet, testosterone levels were lower in the control group by the end of the study (p = 0.007). We observed 1871 distinct proteins in liver tissue, with 77% being common across groups. In gene ontology analysis, no specific pathways were overexpressed. In semiquantitative analysis, we observed differences in proteins associated in lipid metabolism such as Apolipoprotein A-I and Acyl-CoA 6-desaturase, which were lower in the control group (p = 0.024 and p = 0.009). Rats in the intervention groups with weekly playtime displayed the least amount of reported distress during inspection or upon room entry and were less prone to accepting treats. Removing animals from their enclosure was most effortless for those in the large cage group. Over time, there was a decrease in conflicts among rats that interacted only twice weekly during playpen time. DISCUSSION: In summary, refining husbandry practices for aging rats is both simple and budget-friendly, with no apparent adverse effects on stress levels, animal development, or relevant metabolic changes in the liver.

Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.

Monogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Like for other rare diseases, multiple genes have been linked to monogenic diabetes with different measures of pathogenicity, but the information on the genes and variants is not unified among different resources, making it challenging to process them informatically. We have developed an automated pipeline for collecting and harmonizing data on genetic variants linked to monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins linked to monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.

N-glycoproteomic analyses of human intestinal enteroids, varying in histo-blood group geno- and phenotypes, reveal a wide repertoire of fucosylated glycoproteins.

Human noroviruses, globally the main cause of viral gastroenteritis, show strain specific affinity for histo-blood group antigens (HBGA) and can successfully be propagated ex vivo in human intestinal enteroids (HIEs). HIEs established from jejunal stem cells of individuals with different ABO, Lewis and secretor geno- and phenotypes, show varying susceptibility to such infections. Using bottom-up glycoproteomic approaches we have defined and compared the N-linked glycans of glycoproteins of seven jejunal HIEs. Membrane proteins were extracted, trypsin digested, and glycopeptides enriched by hydrophilic interaction liquid chromatography and analyzed by nanoLC-MS/MS. The Byonic software was used for glycopeptide identification followed by hands-on verifications and interpretations. Glycan structures and attachment sites were identified from MS2 spectra obtained by higher-energy collision dissociation through analysis of diagnostic saccharide oxonium ions (B-ions), stepwise glycosidic fragmentation of the glycans (Y-ions), and peptide sequence ions (b- and y-ions). Altogether 694 unique glycopeptides from 93 glycoproteins were identified. The N-glycans encompassed pauci- and oligomannose, hybrid- and complex-type structures. Notably, polyfucosylated HBGA-containing glycopeptides of the four glycoproteins tetraspanin-8, carcinoembryonic antigen-related cell adhesion molecule 5, sucrose-isomaltase and aminopeptidase N were especially prominent and were characterized in detail and related to donor ABO, Lewis and secretor types of each HIE. Virtually no sialylated N-glycans were identified for these glycoproteins suggesting that terminal sialylation was infrequent compared to fucosylation and HBGA biosynthesis. This approach gives unique site-specific information on the structural complexity of N-linked glycans of glycoproteins of human HIEs and provides a platform for future studies on the role of host glycoproteins in gastrointestinal infectious diseases.

StellarPath: Hierarchical-vertical multi-omics classifier synergizes stable markers and interpretable similarity networks for patient profiling.

The Patient Similarity Network paradigm implies modeling the similarity between patients based on specific data. The similarity can summarize patients' relationships from high-dimensional data, such as biological omics. The end PSN can undergo un/supervised learning tasks while being strongly interpretable, tailored for precision medicine, and ready to be analyzed with graph-theory methods. However, these benefits are not guaranteed and depend on the granularity of the summarized data, the clarity of the similarity measure, the complexity of the network's topology, and the implemented methods for analysis. To date, no patient classifier fully leverages the paradigm's inherent benefits. PSNs remain complex, unexploited, and meaningless. We present StellarPath, a hierarchical-vertical patient classifier that leverages pathway analysis and patient similarity concepts to find meaningful features for both classes and individuals. StellarPath processes omics data, hierarchically integrates them into pathways, and uses a novel similarity to measure how patients' pathway activity is alike. It selects biologically relevant molecules, pathways, and networks, considering molecule stability and topology. A graph convolutional neural network then predicts unknown patients based on known cases. StellarPath excels in classification performances and computational resources across sixteen datasets. It demonstrates proficiency in inferring the class of new patients described in external independent studies, following its initial training and testing phases on a local dataset. It advances the PSN paradigm and provides new markers, insights, and tools for in-depth patient profiling.

Proteomic biomarkers in seminal plasma as predictors of reproductive potential in azoospermic men.

Introduction: Azoospermia, characterized by an absence of sperm in the ejaculate, represents the most severe form of male infertility. While surgical sperm retrieval in obstructive azoospermia (OA) is successful in the majority of cases, patients with non-obstructive azoospermia (NOA) show retrieval rates of only about 50% and thus frequently have unnecessary surgery. Surgical intervention could be avoided if patients without preserved spermatogenesis are identified preoperatively. This prospective study aimed to discover biomarkers in seminal plasma that could be employed for a non-invasive differential diagnosis of OA/NOA in order to rationalize surgery recommendations and improve success rates. Methods: All patients signed written informed consent, underwent comprehensive andrological evaluation, received human genetics to exclude relevant pathologies, and patients with azoospermia underwent surgical sperm retrieval. Using label-free LC-MS/MS, we compared the proteomes of seminal plasma samples from fertile men (healthy controls (HC), n=8) and infertile men diagnosed with 1) OA (n=7), 2) NOA with successful sperm retrieval (mixed testicular atrophy (MTA), n=8), and 3) NOA without sperm retrieval (Sertoli cell-only phenotype (SCO), n=7). Relative abundance changes of two candidate markers of sperm retrieval, HSPA2 and LDHC, were confirmed by Western Blot. Results: We found the protein expression levels of 42 proteins to be significantly down-regulated (p ≤ 0.05) in seminal plasma from SCO NOA patients relative to HC whereas only one protein was down-regulated in seminal plasma from MTA patients. Analysis of tissue and cell expression suggested that the testis-specific proteins LDHC, PGK2, DPEP3, and germ-cell enriched heat-shock proteins HSPA2 and HSPA4L are promising biomarkers of spermatogenic function. Western blotting revealed a significantly lower abundance of LDHC and HSPA2 in the seminal plasma of men with NOA (SCO and MTA) compared to controls. Discussion: The results indicate that certain testis-specific proteins when measured in seminal plasma, could serve as indicators of the presence of sperm in the testis and predict the success of sperm retrieval. Used in conjunction with conventional clinical assessments, these proteomic biomarkers may assist in the non-invasive diagnosis of idiopathic male infertility.

Impact of inflammatory preconditioning on murine microglial proteome response induced by focal ischemic brain injury.

Preconditioning with lipopolysaccharide (LPS) induces neuroprotection against subsequent cerebral ischemic injury, mainly involving innate immune pathways. Microglia are resident immune cells of the central nervous system (CNS) that respond early to danger signals through memory-like differential reprogramming. However, the cell-specific molecular mechanisms underlying preconditioning are not fully understood. To elucidate the distinct molecular mechanisms of preconditioning on microglia, we compared these cell-specific proteomic profiles in response to LPS preconditioning and without preconditioning and subsequent transient focal brain ischemia and reperfusion, - using an established mouse model of transient focal brain ischemia and reperfusion. A proteomic workflow, based on isolated microglia obtained from mouse brains by cell sorting and coupled to mass spectrometry for identification and quantification, was applied. Our data confirm that LPS preconditioning induces marked neuroprotection, as indicated by a significant reduction in brain infarct volume. The established brain cell separation method was suitable for obtaining an enriched microglial cell fraction for valid proteomic analysis. The results show a significant impact of LPS preconditioning on microglial proteome patterns by type I interferons, presumably driven by the interferon cluster regulator proteins signal transducer and activator of transcription1/2 (STAT1/2).

Multimodal joint deconvolution and integrative signature selection in proteomics.

Deconvolution is an efficient approach for detecting cell-type-specific (cs) transcriptomic signals without cellular segmentation. However, this type of methods may require a reference profile from the same molecular source and tissue type. Here, we present a method to dissect bulk proteome by leveraging tissue-matched transcriptome and proteome without using a proteomics reference panel. Our method also selects the proteins contributing to the cellular heterogeneity shared between bulk transcriptome and proteome. The deconvoluted result enables downstream analyses such as cs-protein Quantitative Trait Loci (cspQTL) mapping. We benchmarked the performance of this multimodal deconvolution approach through CITE-seq pseudo bulk data, a simulation study, and the bulk multi-omics data from human brain normal tissues and breast cancer tumors, individually, showing robust and accurate cell abundance quantification across different datasets. This algorithm is implemented in a tool MICSQTL that also provides cspQTL and multi-omics integrative visualization, available at https://bioconductor.org/packages/MICSQTL .

Unveiling Cryptosporidium parvum sporozoite-derived extracellular vesicles: profiling, origin, and protein composition.

Cryptosporidium parvum is a common cause of a zoonotic disease and a main cause of diarrhea in newborns. Effective drugs or vaccines are still lacking. Oocyst is the infective form of the parasite; after its ingestion, the oocyst excysts and releases four sporozoites into the host intestine that rapidly attack the enterocytes. The membrane protein CpRom1 is a large rhomboid protease that is expressed by sporozoites and recognized as antigen by the host immune system. In this study, we observed the release of CpRom1 with extracellular vesicles (EVs) that was not previously described. To investigate this phenomenon, we isolated and resolved EVs from the excystation medium by differential ultracentrifugation. Fluorescence flow cytometry and transmission electron microscopy (TEM) experiments identified two types of sporozoite-derived vesicles: large extracellular vesicles (LEVs) and small extracellular vesicles (SEVs). Nanoparticle tracking analysis (NTA) revealed mode diameter of 181 nm for LEVs and 105 nm for SEVs, respectively. Immunodetection experiments proved the presence of CpRom1 and the Golgi protein CpGRASP in LEVs, while immune-electron microscopy trials demonstrated the localization of CpRom1 on the LEVs surface. TEM and scanning electron microscopy (SEM) showed that LEVs were generated by means of the budding of the outer membrane of sporozoites; conversely, the origin of SEVs remained uncertain. Distinct protein compositions were observed between LEVs and SEVs as evidenced by their corresponding electrophoretic profiles. Indeed, a dedicated proteomic analysis identified 5 and 16 proteins unique for LEVs and SEVs, respectively. Overall, 60 proteins were identified in the proteome of both types of vesicles and most of these proteins (48 in number) were already identified in the molecular cargo of extracellular vesicles from other organisms. Noteworthy, we identified 12 proteins unique to Cryptosporidium spp. and this last group included the immunodominant parasite antigen glycoprotein GP60, which is one of the most abundant proteins in both LEVs and SEVs.

FBXO32-mediated degradation of PTEN promotes lung adenocarcinoma progression.

FBXO32, a member of the F-box protein family, is known to play both oncogenic and tumor-suppressive roles in different cancers. However, the functions and the molecular mechanisms regulated by FBXO32 in lung adenocarcinoma (LUAD) remain unclear. Here, we report that FBXO32 is overexpressed in LUAD compared with normal lung tissues, and high expression of FBXO32 correlates with poor prognosis in LUAD patients. Firstly, we observed with a series of functional experiments that FBXO32 alters the cell cycle and promotes the invasion and metastasis of LUAD cells. We further corroborate our findings using in vivo mouse models of metastasis and confirmed that FBXO32 positively regulates LUAD tumor metastasis. Using a proteomic-based approach combined with computational analyses, we found a positive correlation between FBXO32 and the PI3K/AKT/mTOR pathway, and identified PTEN as a FBXO32 interactor. More important, FBXO32 binds PTEN via its C-terminal substrate binding domain and we also validated PTEN as a bona fide FBXO32 substrate. Finally, we demonstrated that FBXO32 promotes EMT and regulates the cell cycle by targeting PTEN for proteasomal-dependent degradation. In summary, our study highlights the role of FBXO32 in promoting the PI3K/AKT/mTOR pathway via PTEN degradation, thereby fostering lung adenocarcinoma progression.