Secretomics—A Key to a Comprehensive Picture of Unconventional Protein Secretion

Mustn1 is a smooth muscle cell-secreted microprotein that modulates skeletal muscle extracellular matrix composition

OBJECTIVE

Skeletal muscle plasticity and remodeling are critical for adapting tissue function to use, disuse, and regeneration. The aim of this study was to identify genes and molecular pathways that regulate the transition from atrophy to compensatory hypertrophy or recovery from injury. Here, we have used a mouse model of hindlimb unloading and reloading, which causes skeletal muscle atrophy, and compensatory regeneration and hypertrophy, respectively.

METHODS

We analyzed mouse skeletal muscle at the transition from hindlimb unloading to reloading for changes in transcriptome and extracellular fluid proteome. We then used qRT-PCR, immunohistochemistry, and bulk and single-cell RNA sequencing data to determine Mustn1 gene and protein expression, including changes in gene expression in mouse and human skeletal muscle with different challenges such as exercise and muscle injury. We generated Mustn1-deficient genetic mouse models and characterized them in vivo and ex vivo with regard to muscle function and whole-body metabolism. We isolated smooth muscle cells and functionally characterized them, and performed transcriptomics and proteomics analysis of skeletal muscle and aorta of Mustn1-deficient mice.

RESULTS

We show that Mustn1 (Musculoskeletal embryonic nuclear protein 1, also known as Mustang) is highly expressed in skeletal muscle during the early stages of hindlimb reloading. Mustn1 expression is transiently elevated in mouse and human skeletal muscle in response to intense exercise, resistance exercise, or injury. We find that Mustn1 expression is highest in smooth muscle-rich tissues, followed by skeletal muscle fibers. Muscle from heterozygous Mustn1-deficient mice exhibit differences in gene expression related to extracellular matrix and cell adhesion, compared to wild-type littermates. Mustn1-deficient mice have normal muscle and aorta function and whole-body glucose metabolism. We show that Mustn1 is secreted from smooth muscle cells, and that it is present in arterioles of the muscle microvasculature and in muscle extracellular fluid, particularly during the hindlimb reloading phase. Proteomics analysis of muscle from Mustn1-deficient mice confirms differences in extracellular matrix composition, and female mice display higher collagen content after chemically induced muscle injury compared to wild-type littermates.

CONCLUSIONS

We show that, in addition to its previously reported intracellular localization, Mustn1 is a microprotein secreted from smooth muscle cells into the muscle extracellular space. We explore its role in muscle ECM deposition and remodeling in homeostasis and upon muscle injury. The role of Mustn1 in fibrosis and immune infiltration upon muscle injury and dystrophies remains to be investigated, as does its potential for therapeutic interventions.

Assessing the risk to develop a growing teratoma syndrome based on molecular and epigenetic subtyping as well as novel secreted biomarkers

In germ cell tumors (GCT), a growing teratoma during chemotherapy with decreasing tumor markers was defined as 'growing teratoma syndrome' (GTS) by Logothetis et al. in 1982. So far, its pathogenesis and specific treatment options remain elusive. We aimed at updating the GTS definition based on molecular and epigenetic features as well as identifying circulating biomarkers. We selected 50 GTS patients for clinical characterization and subsequently 12 samples were molecularly analyzed. We further included 7 longitudinal samples of 2 GTS patients. Teratomas (TER) showing no features of GTS served as controls. GTS were stratified based on growth rates into a slow (<0.5 cm/month), medium (0.5-1.5) and rapid (>1.5) group. By analyzing DNA methylation, microRNA expression and the secretome, we identified putative epigenetic and secreted biomarkers for the GTS subgroups. We found that proteins enriched in the GTS groups compared to TER were involved in proliferation, DNA replication and the cell cycle, while proteins interacting with the immune system were depleted. Additionally, GTSrapid seem to interact more strongly with the surrounding microenvironment than GTSslow. Expression of pluripotency- and yolk-sac tumor-associated genes in GTS and formation of a yolk-sac tumor or somatic-type malignancy in the longitudinal GTS samples, pointed at an additional occult non-seminomatous component after chemotherapy. Thus, updating the Logothetis GTS definition is necessary, which we propose as follows: The GTS describes a continuously growing teratoma that might harbor occult non-seminomatous components considerably reduced during therapy but outgrowing over time again.

NCSP-PLM: An ensemble learning framework for predicting non-classical secreted proteins based on protein language models and deep learning

Non-classical secreted proteins (NCSPs) refer to a group of proteins that are located in the extracellular environment despite the absence of signal peptides and motifs. They usually play different roles in intercellular communication. Therefore, the accurate prediction of NCSPs is a critical step to understanding in depth their associated secretion mechanisms. Since the experimental recognition of NCSPs is often costly and time-consuming, computational methods are desired. In this study, we proposed an ensemble learning framework, termed NCSP-PLM, for the identification of NCSPs by extracting feature embeddings from pre-trained protein language models (PLMs) as input to several fine-tuned deep learning models. First, we compared the performance of nine PLM embeddings by training three neural networks: Multi-layer perceptron (MLP), attention mechanism and bidirectional long short-term memory network (BiLSTM) and selected the best network model for each PLM embedding. Then, four models were excluded due to their below-average accuracies, and the remaining five models were integrated to perform the prediction of NCSPs based on the weighted voting. Finally, the 5-fold cross validation and the independent test were conducted to evaluate the performance of NCSP-PLM on the benchmark datasets. Based on the same independent dataset, the sensitivity and specificity of NCSP-PLM were 91.18% and 97.06%, respectively. Particularly, the overall accuracy of our model achieved 94.12%, which was 7~16% higher than that of the existing state-of-the-art predictors. It indicated that NCSP-PLM could serve as a useful tool for the annotation of NCSPs.

Seeking the interspecies crosswalk for filamentous microbe effectors

Both pathogenic and symbiotic microorganisms modulate the immune response and physiology of their host to establish a suitable niche. Key players in mediating colonization outcome are microbial effector proteins that act either inside (cytoplasmic) or outside (apoplastic) the plant cells and modify the abundance or activity of host macromolecules. We compile novel insights into the much-disputed processes of effector secretion and translocation of filamentous organisms, namely fungi and oomycetes. We report how recent studies that focus on unconventional secretion and effector structure challenge the long-standing image of effectors as conventionally secreted proteins that are translocated with the aid of primary amino acid sequence motifs. Furthermore, we emphasize the potential of diverse, unbiased, state-of-the-art proteomics approaches in the holistic characterization of fungal and oomycete effectomes.

Dynamic mapping of proteome trafficking within and between living cells by TransitID

The ability to map trafficking for thousands of endogenous proteins at once in living cells would reveal biology currently invisible to both microscopy and mass spectrometry. Here, we report TransitID, a method for unbiased mapping of endogenous proteome trafficking with nanometer spatial resolution in living cells. Two proximity labeling (PL) enzymes, TurboID and APEX, are targeted to source and destination compartments, and PL with each enzyme is performed in tandem via sequential addition of their small-molecule substrates. Mass spectrometry identifies the proteins tagged by both enzymes. Using TransitID, we mapped proteome trafficking between cytosol and mitochondria, cytosol and nucleus, and nucleolus and stress granules (SGs), uncovering a role for SGs in protecting the transcription factor JUN from oxidative stress. TransitID also identifies proteins that signal intercellularly between macrophages and cancer cells. TransitID offers a powerful approach for distinguishing protein populations based on compartment or cell type of origin.

Modulation of cellular transcriptome and proteome composition by azidohomoalanine-implications on click chemistry-based secretome analysis

The analysis of the secretome provides important information on proteins defining intercellular communication and the recruitment and behavior of cells in specific tissues. Especially in the context of tumors, secretome data can support decisions for diagnosis and therapy. The mass spectrometry-based analysis of cell-conditioned media is widely used for the unbiased characterization of cancer secretomes in vitro. Metabolic labeling using azide-containing amino acid analogs in combination with click chemistry facilitates this type of analysis in the presence of serum, preventing serum starvation-induced effects. The modified amino acid analogs, however, are less efficiently incorporated into newly synthesized proteins and may perturb protein folding. Combining transcriptome and proteome analysis, we elucidate in detail the effects of metabolic labeling with the methionine analog azidohomoalanine (AHA) on gene and protein expression. Our data reveal that 15-39% of the proteins detected in the secretome displayed changes in transcript and protein expression induced by AHA labeling. Gene Ontology (GO) analyses indicate that metabolic labeling using AHA leads to induction of cellular stress and apoptosis-related pathways and provide first insights on how this affects the composition of the secretome on a global scale. KEY MESSAGES: Azide-containing amino acid analogs affect gene expression profiles. Azide-containing amino acid analogs influence cellular proteome. Azidohomoalanine labeling induces cellular stress and apoptotic pathways. Secretome consists of proteins with dysregulated expression profiles.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

Identification of secreted proteins by comparison of protein abundance in conditioned media and cell lysates

Analysis of the full spectrum of secreted proteins in cell culture is complicated by leakage of intracellular proteins from damaged cells. To address this issue, we compared the abundance of individual proteins between the cell lysate and the conditioned medium, reasoning that secreted proteins should be relatively more abundant in the conditioned medium. Marked enrichment for signal-peptide-bearing proteins with increasing conditioned media to cell lysate ratio, as well loss of this signal following brefeldin A treatment, confirmed the sensitivity and specificity of this approach. The subset of proteins demonstrating increased conditioned media to cell lysate ratio in the presence of Brefeldin A identified candidates for unconventional secretion via a pathway independent of ER to Golgi trafficking.