Methodologies to decipher the cell secretome

In silico identification of drug targets and vaccine candidates against Bartonella quintana: a subtractive proteomics approach

BACKGROUND

The availability of genes and protein sequences for parasites has provided valuable information for drug target identification and vaccine development. One such parasite is Bartonella quintana, a Gram-negative, intracellular pathogen that causes bartonellosis in mammalian hosts.

OBJECTIVE

Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to B. quintana.

METHODS AND FINDINGS

To explore these aspects, we have adopted a subtractive proteomics approach to analyse the proteome of B. quintana. By subtractive proteins between the host and parasite proteome, a set of proteins that are likely unique to the parasite but absent in the host were identified. This analysis revealed that out of the 1197 protein sequences of the parasite, 660 proteins are non-homologous to the human host. Further analysis using the Database of Essential Genes predicted 159 essential proteins, with 28 of these being unique to the pathogen and predicted as potential putative targets. Subcellular localisation of the predicted targets revealed 13 cytoplasmic, eight membranes, one periplasmic, and multiple location proteins. The three-dimensional structure and B cell epitopes of the six membrane antigenic protein were predicted. Four B cell epitopes in KdtA and mraY proteins, three in lpxB and BQ09550, whereas the ftsl and yidC proteins were located with eleven and six B cell epitopes, respectively.

MAINS CONCLUSIONS

This insight prioritises such proteins as novel putative targets for further investigations on their potential as drug and vaccine candidates.

Recent advances of nanopore technique in single cell analysis

Single cells and their dynamic behavior are closely related to biological research. Monitoring their dynamic behavior is of great significance for disease prevention. How to achieve rapid and non-destructive monitoring of single cells is a major issue that needs to be solved urgently. As an emerging technology, nanopores have been proven to enable non-destructive and label-free detection of single cells. The structural properties of nanopores enable a high degree of sensitivity and accuracy during analysis. In this article, we summarize and classify the different types of solid-state nanopores that can be used for single-cell detection and illustrate their specific applications depending on the size of the analyte. In addition, their research progress in material transport and microenvironment monitoring is also highlighted. Finally, a brief summary of existing research challenges and future trends in nanopore single-cell analysis is tentatively provided.

Machine Learning-Assisted High-Throughput SERS Classification of Cell Secretomes

During the response to different stress conditions, damaged cells react in multiple ways, including the release of a diverse cocktail of metabolites. Moreover, secretomes from dying cells can contribute to the effectiveness of anticancer therapies and can be exploited as predictive biomarkers. The nature of the stress and the resulting intracellular responses are key determinants of the secretome composition, but monitoring such processes remains technically arduous. Hence, there is growing interest in developing tools for noninvasive secretome screening. In this regard, it has been previously shown that the relative concentrations of relevant metabolites can be traced by surface-enhanced Raman scattering (SERS), thereby allowing label-free biofluid interrogation. However, conventional SERS approaches are insufficient to tackle the requirements imposed by high-throughput modalities, namely fast data acquisition and automatized analysis. Therefore, machine learning methods were implemented to identify cell secretome variations while extracting standard features for cell death classification. To this end, ad hoc microfluidic chips were devised, to readily conduct SERS measurements through a prototype relying on capillary pumps made of filter paper, which eventually would function as the SERS substrates. The developed strategy may pave the way toward a faster implementation of SERS into cell secretome classification, which can be extended even to laboratories lacking highly specialized facilities.

An Introduction to Analytical Challenges, Approaches, and Applications in Mass Spectrometry-Based Secretomics

The active release of proteins into the extracellular space and the proteolytic cleavage of cell surface proteins are key processes that coordinate and fine-tune a multitude of physiological functions. The entirety of proteins that fulfill these extracellular tasks are referred to as the secretome and are of special interest for the investigation of biomarkers of disease states and physiological processes related to cell-cell communication. LC-MS-based proteomics approaches are a valuable tool for the comprehensive and unbiased characterization of this important subproteome. This review discusses procedures, opportunities, and limitations of mass spectrometry-based secretomics to better understand and navigate the complex analytical landscape for studying protein secretion in biomedical science.

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.

Breast cancer cell secretome analysis to decipher miRNA regulating the tumor microenvironment and discover potential biomarkers

MicroRNA (miRNA/miR) 526 b- and miR655-overexpressed tumor cell-free secretions regulate the breast cancer tumor microenvironment (TME) by promoting tumor-associated angiogenesis, oxidative stress, and hypoxic responses. Additionally, premature miRNA (pri-miR526b and pri-miR655) are established breast cancer blood biomarkers. However, the mechanisms of how these miRNAs regulate the TME has yet to be investigated. Mass spectrometry analysis of miRNA-overexpressed cell lines MCF7-miR526b, MCF7-miR655, and miRNA-low MCF7-Mock cell-free secretomes identified 34 differentially expressed proteins coded by eight genes. In both miRNA-high cell secretomes, four markers are upregulated: YWHAB, SFN, TXNDC12, and MYL6B, and four are downregulated: PEA15, PRDX4, PSMB6, and FN1. All upregulated marker transcripts are significantly high in both total cellular RNA pool and cell-free secretions of miRNA-high cell lines, validated with quantitative RT-PCR. Bioinformatics tools were used to investigate these markers' roles in breast cancer. These markers' top gene ontology functions are related to apoptosis, oxidative stress, membrane transport, and motility supporting oncogenic miR526b- and miR655-induced functions. Gene transcription factor analysis tools were used to show how these miRNAs regulate the expression of each secretory marker. Data extracted from the Human Protein Atlas showed that YWHAB, SFN, and TXNDC12 expression could distinguish early and late-stage breast cancer in various breast cancer subtypes and are associated with poor patient survival. Additionally, immunohistochemistry analysis showed the expression of each marker in breast tumors. A stronger correlation between miRNA clusters and upregulated secretory markers gene expression was found in the luminal A tumor subtype. YWHAB, SFN, and MYL6B are upregulated in breast cancer patient's blood, showing biomarker potential. Of these identified novel miRNA secretory markers, SFN and YWHAB successfully passed all validations and are the best candidates to further investigate their roles in miRNA associated TME regulation. Also, these markers show the potential to serve as blood-based breast cancer biomarkers, especially for luminal-A subtypes.

Advanced molecular therapies for neurological diseases: focus on stroke, alzheimer's disease, and parkinson's disease

Neurological diseases (NDs) are one of the leading causes of disability and the second leading cause of death globally. Among these stroke, Alzheimer's disease (AD), and Parkinson's disease (PD) are the most common NDs. A rise in the absolute number of individuals affected with these diseases indicates that the current treatment strategies in management and prevention of these debilitating diseases are not effective sufficiently. Therefore, novel treatment strategies are being explored to cure these diseases by addressing the causative mechanisms at the molecular level. Advanced therapies like gene therapy (gene editing and gene silencing) and stem cell therapies aim to cure diseases by gene editing, gene silencing and tissue regeneration, respectively. Gene editing results in the deletion of the aberrant gene or insertion of the corrected gene which can be executed using the CRISPR/Cas gene editing tool a promising treatment strategy being explored for many other prevalent diseases. Gene silencing using siRNA silences the gene by inhibiting protein translation, thereby silencing its expression. Stem cell therapy aims to regenerate damaged cells or tissues because of their ability to divide into any type of cell in the human body. Among these approaches, gene editing and gene silencing have currently been applied in vitro and to animal models, while stem cell therapy has reached the clinical trial stage for the treatment of NDs. The current status of these strategies suggests a promising outcome in their clinical translation.

Cancer secretome: finding out hidden messages in extracellular secretions

Secretome analysis has gained popularity recently as a very well-designed proteomic approach that is being used to study various interactions and their effects on cellular activity. This analysis is especially helpful while studying the effects of the cells on their microenvironment, paracrine and autocrine processes, their therapeutic purposes, and as a new diagnostic perspective. Cancer is a condition rather than a specific type of disease and is still yet to be fully understood. Cancer secretome is a fairly new concept that is being implemented to examine the interactions taking place in the tumor microenvironment and can help to understand the phenomena like induction of tumorigenesis, stimulation of immune cells, etc. The secretome analysis helps to gain a different perspective on the existing knowledge on cancer and its effects. The recent advances in secretome studies are directed toward secreted components as drug targets, biomarkers, and companion tools for diagnostic and prognostic purposes in cancer. This review aims to find the interactors in different types of cancer and understand the existing unstructured secretome data and its application in prognosis, diagnosis, and in biomarker study.

Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases

Proteomics is playing an increasingly important role in identifying pathogens, emerging and re-emerging infectious agents, understanding pathogenesis, and diagnosis of diseases. Recently, more advanced and sophisticated proteomics technologies have transformed disease diagnostics and vaccines development. The detection of pathogens is made possible by more accurate and time-constrained technologies, resulting in an early diagnosis. More detailed and comprehensive information regarding the proteome of any noxious agent is made possible by combining mass spectrometry with various gel-based or short-gun proteomics approaches recently. MALDI-ToF has been proved quite useful in identifying and distinguishing bacterial pathogens. Other quantitative approaches are doing their best to investigate bacterial virulent factors, diagnostic markers and vaccine candidates. Proteomics is also helping in the identification of secreted proteins and their virulence-related functions. This review aims to highlight the role of cutting-edge proteomics approaches in better understanding the functional genomics of pathogens. This also underlines the limitations of proteomics in bacterial secretome research.

Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases

Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.

Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease

BACKGROUND

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less is known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD.

RESULTS

The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix and vascular remodeling.

CONCLUSIONS

The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes.

Interval-Based Secretomics Unravels Acute-Phase Response in Hepatocyte Model Systems

Mass spectrometry-based secretomics approaches frequently utilize serum-free culture conditions to circumvent serum-induced interference and to increase analytical depth. However, this can negatively affect a wide range of cellular functions and cell viability. These effects become particularly apparent when investigating transcriptionally regulated secretion events and feedback-loops in response to perturbations that require 48 h or more to fully manifest. We present an “interval-based” secretomics workflow, which determines protein secretion rates in short serum-free time windows. Relative quantification using tandem mass tags enables precise monitoring of time-dependent changes. We applied this approach to determine temporal profiles of protein secretion in the hepatocyte model cell lines HepG2 and HepaRG after stimulation of the acute-phase response (APR) by the cytokines IL1b and IL6. While the popular hepatocarcinoma cell line HepG2 showed an incomplete APR, secretion patterns derived from differentiated HepaRG cells recapitulated the expected APR more comprehensively. For several APR response proteins, substantial secretion was only observed after 72 h, a time window at which cell fitness is substantially impaired under serum-free cell culture conditions. The interval-based secretomics approach enabled the first comprehensive analysis of time-dependent secretion of liver cell models in response to these proinflammatory cytokines. The extended time range facilitated the observation of distinct chronological phases and cytokine-dependent secretion phenotypes of the APR. IL1b directed the APR toward pathogen defense over three distinct phases—chemotaxis, effector, clearance—while IL6 directed the APR toward regeneration. Protein shedding on the cell surface was pronounced upon IL1b stimulation, and small molecule inhibition of ADAM and matrix metalloproteases identified induced as well as constitutive shedding events. Inhibition of ADAM proteases with TAPI-0 resulted in reduced shedding of the sorting receptor SORT1, and an attenuated cytokine response suggesting a direct link between cell surface shedding and cytokine secretion rates.

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Interval-based secretomics enables extended time course analysis.

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Time-resolved acute phase response in liver model systems HepG2 and HepaRG.

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IL1b response clusters in three phases.

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Cell surface shedding is amplified during acute-phase response.

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ADAM inhibition dampens secretion of inflammatory cytokines.

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

For a long time, leaderless secreted proteins (LLSP) were neglected as artifacts derived from dying cells. It is now generally accepted that secretion of LLSP–as a part of the collective term unconventional protein secretion (UPS) - is an evolutionarily conserved process and that these LLSP are actively and selectively secreted from living cells bypassing the classical endoplasmic reticulum-Golgi pathway. However, the mechanism of UPS pathways, as well as the number of LLSP and which part of a protein is involved in the selection of LLSPs for secretion, are still enigmatic and await clarification. Secretomics-a proteomics-based approach to identify and quantify all proteins secreted by a cell-is inherently unbiased toward a particular secretion pathway and offers the opportunity to shed light on the UPS. Here, we will evaluate and present recent results of proteomic workflows allowing to obtain high-confident secretome data. Additionally, we address that cell culture conditions largely affect the composition of the secretome. This has to be kept in mind to control cell culture induced artifacts and adaptation stress in serum free conditions. Evaluation of click chemistry for secretome analysis of cells under serum-containing conditions showed a significant change in the cellular proteome with longer incubation time upon treatment with non-canonical amino acid azidohomoalanine. Finally, we showed that the number of LLSP far exceeds the number of secreted proteins annotated in Uniprot and ProteinAtlas. Thus, secretomics in combination with sophisticated microbioanalytical and sample preparation methods is well suited to provide a comprehensive picture of UPS.

Label-Free Quantitative Proteomics to Explore the Action Mechanism of the Pharmaceutical-Grade Triticum vulgare Extract in Speeding Up Keratinocyte Healing

Plant extracts have shown beneficial properties in terms of skin repair, promoting wound healing through a plethora of mechanisms. In particular, the poly-/oligosaccharidic aqueous extract of Triticum vulgare (TVE), as well as TVE-based products, shows interesting biological assets, hastening wound repair. Indeed, TVE acts in the treatment of tissue regeneration mainly on decubitus and venous leg ulcers. Moreover, on scratched monolayers, TVE prompts HaCat cell migration, correctly modulating the expression of metalloproteases toward a physiological matrix remodeling. Here, using the same HaCat-based in vitro scratch model, the TVE effect has been investigated thanks to an LFQ proteomic analysis of HaCat secretomes and immunoblotting. Indeed, the unbiased TVE effect on secreted proteins has not yet been fully understood, and it could be helpful to obtain a comprehensive picture of its bio-pharmacological profile. It has emerged that TVE treatment induces significant up-regulation of several proteins in the secretome (153 to be exact) whereas only a few were down-regulated (72 to be exact). Interestingly, many of the up-regulated proteins are implicated in promoting wound-healing-related processes, such as modulating cell-cell interaction and communication, cell proliferation and differentiation, and prompting cell adhesion and migration.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

Proteomic changes in the extracellular environment of sea bass thymocytes exposed to 17α-ethinylestradiol in vitro

The thymus is an important immune organ providing the necessary microenvironment for the development of a diverse, self-tolerant T cell repertoire, which is selected to allow for the recognition of foreign antigens while avoiding self-reactivity. Thymus function and activity are known to be regulated by sex steroid hormones, such as oestrogen, leading to sexual dimorphisms in immunocompetence between males and females. The oestrogenic modulation of the thymic function provides a potential target for environmental oestrogens, such as 17α-ethynylestradiol (EE2), to interfere with the cross-talk between the endocrine and the immune system. Oestrogen receptors have been identified on thymocytes and the thymic microenvironment, but it is unclear how oestrogens regulate thymic epithelial and T cell communication including paracrine signalling. Much less is known regarding intrathymic signalling in fish. Secretomics allows for the analysis of complex mixtures of immunomodulatory signalling factors secreted by T cells. Thus, in the present study, isolated thymocytes of the European sea bass, Dicentrarchus labrax, were exposed in vitro to 30 nM EE2 for 4 h and the T cell-secretome (i.e., extracellular proteome) was analysed by quantitative label-free mass-spectrometry. Progenesis revealed a total of 111 proteins differentially displayed between EE2-treated and control thymocytes at an α-level of 5% and a 1.3-fold change cut off (n = 5-6). The EE2-treatment significantly decreased the level of 90 proteins. Gene ontology revealed the proteasome to be the most impacted pathway. In contrast, the abundance of 21 proteins was significantly increased, with cathepsins showing the highest level of induction. However, no particular molecular pathway was significantly altered for these upregulated proteins. To the best of our knowledge, this work represents the first study of the secretome of the fish thymus exposed to the environmental oestrogen EE2, highlighting the impact on putative signalling pathways linked to immune surveillance, which may be of crucial importance for fish health and defence against pathogens.

Tumor Secretome to Adoptive Cellular Immunotherapy: Reduce Me Before I Make You My Partner

Adoptive cellular immunotherapy using chimeric antigen receptor (CAR)-modified T cells and Natural Killer (NK) cells are common immune cell sources administered to treat cancer patients. In detail, whereas CAR-T cells induce outstanding responses in a subset of hematological malignancies, responses are much more deficient in solid tumors. Moreover, NK cells have not shown remarkable results up to date. In general, immune cells present high plasticity to change their activity and phenotype depending on the stimuli they receive from molecules secreted in the tumor microenvironment (TME). Consequently, immune cells will also secrete molecules that will shape the activities of other neighboring immune and tumor cells. Specifically, NK cells can polarize to activities as diverse as angiogenic ones instead of their killer activity. In addition, tumor cell phagocytosis by macrophages, which is required to remove dying tumor cells after the attack of NK cells or CAR-T cells, can be avoided in the TME. In addition, chemotherapy or radiotherapy treatments can induce senescence in tumor cells modifying their secretome to a known as “senescence-associated secretory phenotype” (SASP) that will also impact the immune response. Whereas the SASP initially attracts immune cells to eliminate senescent tumor cells, at high numbers of senescent cells, the SASP becomes detrimental, impacting negatively in the immune response. Last, CAR-T cells are an attractive option to overcome these events. Here, we review how molecules secreted in the TME by either tumor cells or even by immune cells impact the anti-tumor activity of surrounding immune cells.

Gliome database: a comprehensive web-based tool to access and analyze glia secretome data

Glial cells are phenotypically heterogeneous non-neuronal components of the central and peripheral nervous systems. These cells are endowed with diverse functions and molecular machineries to detect and regulate neuronal or their own activities by various secreted mediators, such as proteinaceous factors. In particular, glia-secreted proteins form a basis of a complex network of glia-neuron or glia-glia interactions in health and diseases. In recent years, the analysis and profiling of glial secretomes have raised new expectations for the diagnosis and treatment of neurological disorders due to the vital role of glia in numerous physiological or pathological processes of the nervous system. However, there is no online database of glia-secreted proteins available to facilitate glial research. Here, we developed a user-friendly 'Gliome' database (available at www.gliome.org), a web-based tool to access and analyze glia-secreted proteins. The database provides a vast collection of information on 3293 proteins that are released from glia of multiple species and have been reported to have differential functions under diverse experimental conditions. It contains a web-based interface with the following four key features regarding glia-secreted proteins: (i) fundamental information, such as signal peptide, SecretomeP value, functions and Gene Ontology category; (ii) differential expression patterns under distinct experimental conditions; (iii) disease association; and (iv) interacting proteins. In conclusion, the Gliome database is a comprehensive web-based tool to access and analyze glia-secretome data obtained from diverse experimental settings, whereby it may facilitate the integration of bioinformatics into glial research.

Quantitative MS Workflow for a High-Quality Secretome Analysis by a Quantitative Secretome-Proteome Comparison

Cells secrete proteins to communicate with their environment. Therefore, it is interesting to characterize the proteins which are released from cells under certain experimental conditions the so-called secretome. Here, often proteins from conditioned medium of cultured cells are analyzed, but these additionally might include also contaminating proteins of serum that have not been sufficiently removed or proteins from dying cells. To provide high-quality secretome data and minimize potential contaminants, we describe a quantitative comparison of conditioned medium and the cellular proteome. The described workflow comprises cell cultivation, sample preparation, and final data analysis which is based on the comparison of data from label-free mass spectrometric quantification of proteins from the conditioned medium with corresponding cellular proteomes enabling the detection of bona fide secreted proteins.

Foodborne pathogens in the omics era

Outbreaks and deaths related to Foodborne Diseases (FBD) occur constantly in the world, as a result of the consumption of contaminated foodstuffs with pathogens such as Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Salmonella spp, Clostridium spp. and Campylobacter spp. The purpose of this review is to discuss the main omic techniques applied in foodborne pathogen and to demonstrate their functionalities through the food chain and to guarantee the food safety. The main techniques presented are genomic, transcriptomic, secretomic, proteomic, and metabolomic, which together, in the field of food and nutrition, are known as "Foodomics." This review had highlighted the potential of omics to integrate variables that contribute to food safety and to enable us to understand their application on foodborne diseases. The appropriate use of these techniques had driven the definition of critical parameters to achieve successful results in the improvement of consumers health, costs and to obtain safe and high-quality products.

Oncolytic Virus Therapy Alters the Secretome of Targeted Glioblastoma Cells

Simple Summary

Proteins secreted by cancer cells in response to oncolytic virus anti-tumor therapy constitute the instructions for the immune cells. Yet as there are hundreds of proteins, including those encapsulated in vesicles, whose message drives the mobilization of immune cells, we aimed to decipher the instruction sent by cancer cells in response to therapy. Searching the cataloged vesicle and vesicle-free secreted proteins, we found that the proteins associated with the favorable survival of brain cancer patients were those that have the power to mobilize the immune cells. Thus, this approach established cancer-secreted contributors to the immune–therapeutic effect of the oncolytic virus.

Abstract

Oncolytic virus (OV) therapy, which is being tested in clinical trials for glioblastoma, targets cancer cells, while triggering immune cells. Yet OV sensitivity varies from patient to patient. As OV therapy is regarded as an anti-tumor vaccine, by making OV-infected cancer cells secrete immunogenic proteins, linking these proteins to transcriptome would provide a measuring tool to predict their sensitivity. A set of six patient-derived glioblastoma cells treated ex-vivo with herpes simplex virus type 1 (HSV1) modeled a clinical setting of OV infection. The cellular transcriptome and secreted proteome (separated into extracellular vesicles (EV) and EV-depleted fractions) were analyzed by gene microarray and mass-spectroscopy, respectively. Data validation and in silico analysis measured and correlated the secretome content with the response to infection and patient survival. Glioblastoma cells reacted to the OV infection in a seemingly dissimilar fashion, but their transcriptomes changed in the same direction. Therefore, the upregulation of transcripts encoding for secreted proteins implies a common thread in the response of cancer cells to infection. Indeed, the OV-driven secretome is linked to the immune response. While these proteins have distinct membership in either EV or EV-depleted fractions, it is their co-secretion that augments the immune response and associates with favorable patient outcomes.

Emergence of the Stem Cell Secretome in Regenerative Engineering

The secretome is defined as the set of molecules and biological factors that are secreted by cells into the extracellular space. In the past decade, secretome-based therapies have emerged as a promising approach to overcome the limitations associated with cell-based therapies for tissue and organ regeneration. Considering the growing number of recent publications related to secretome-based therapies, this review takes a step-by-step engineering approach to evaluate the role of the stem cell secretome in regenerative engineering. We discuss the functional benefits of the secretome, the techniques used to engineer the secretome and tailor its therapeutic effects, and the delivery systems and strategies that have been developed to use the secretome for tissue regeneration.

Comparative Secretomics Gives Access to High Confident Secretome Data: Evaluation of Different Methods for the Determination of Bona Fide Secreted Proteins

Secretome analysis is broadly applied to understand the interplay between cells and their microenvironment. In particular, the unbiased analysis by mass spectrometry-based proteomics of conditioned medium has been successfully applied. In this context, several approaches have been developed allowing to distinguish proteins actively secreted by cells from proteins derived from culture medium or proteins released from dying cells. Here, three different methods comparing conditioned medium and lysate by quantitative mass spectrometry-based proteomics to identify bona fide secreted proteins are evaluated. Evaluation in three different human cell lines reveals that all three methods give access to a similar set of bona fide secreted proteins covering a broad abundance range. In the analyzed primary cells, that is, mesenchymal stromal cells and normal human dermal fibroblasts, more than 70% of the identified proteins are linked to classical secretion pathways. Furthermore, 4-12% are predicted to be released by unconventional secretion pathways. Interestingly, evidence of release by ectodomain shedding in a large number of the remaining candidate proteins is found. In summary, it is convinced that comparative secretomics is currently the method of choice to obtain high-confident secretome data and to identify novel candidates for unconventional protein secretion which have been neglected so far.

Localized Cell-Surface Sampling of a Secreted Factor Using Cell-Targeting Beads

Intercellular communication through the secretion of soluble factors plays a vital role in a wide range of biological processes (e.g., homeostasis, immune response), yet identification and quantification of many of these factors can be challenging due to their degradation or sequestration in cell culture media prior to analysis. Here, we present a customizable bead-based system capable of simultaneously binding to live cells (through antibody-mediated cell tethering) and capturing cell-secreted molecules. Our functionalized beads capture secreted molecules (e.g., hepatocyte growth factor secreted by fibroblasts) that are diminished when sampled via traditional supernatant analysis techniques (p < 0.05), effectively rescuing a reduced signal in the presence of neutralizing components in the cell culture media. Our system enables capture and analysis of molecules integral to chemical communication that would otherwise be markedly decreased prior to analysis.

In Silico Identification of Novel Immunogenic Secreted Proteins of Mycoplasma bovis from Secretome Data and Experimental Verification

Mycoplasma bovis is a major pathogen, responsible for bovine respiratory diseases worldwide. The present lack of effective control measures leaves cattle owners at considerable perpetual risk of M. bovis outbreaks. In this study, we identified M. bovis secreted immunogenic proteins in silico as potential candidates for novel diagnostic agents and vaccines. We used immunoinformatics to analyze 438 M. bovis proteins previously identified with a label-free proteomics analysis of virulent M. bovis HB0801 (P1) and its attenuated P150 strains. The subcellular localization of these proteins was preliminarily screened and 59 proteins were found to be secreted extracellular proteins. Twenty-seven of these proteins contained a large number of predictive T-cell epitopes presented by major histocompatibility complex (MHC) class I and II molecules. Twenty-two of these 27 proteins had a high number of conformational B-cell epitopes, predicted from the corresponding 3D structural templates, including one unique to P1, two unique to P150, and 19 common to both strains. Five proteins were selected for further validation, and two of these, MbovP274 and MbovP570, were successfully expressed and purified. Both were confirmed to be secretory and highly immunogenic proteins that induced a mouse antibody response, reacted with cattle serum positive for M. bovis infection, and significantly increased the production of interleukin 8 (IL-8), IL-12 and interferon γ (IFN-γ) during the secretion of these three cytokines by both M. bovis mutants of these genes. These results should be useful in the development of novel immunological agents against M. bovis infection.

The expression landscape of cachexia-inducing factors in human cancers

BACKGROUND

Cachexia is a multifactorial syndrome highly associated with specific tumour types, but the causes of variation in cachexia prevalence and severity are unknown. While circulating plasma mediators (soluble cachectic factors) derived from tumours have been implicated with the pathogenesis of the syndrome, these associations were generally based on plasma concentration rather than tissue-specific gene expression levels. Here, we hypothesized that tumour gene expression profiling of cachexia-inducing factors (CIFs) in human cancers with different prevalence of cachexia could reveal potential cancer-specific cachexia mediators and biomarkers of clinical outcome.

METHODS

First, we combined uniformly processed RNA sequencing data from The Cancer Genome Atlas and Genotype-Tissue Expression databases to characterize the expression profile of secretome genes in 12 cancer types (4651 samples) compared with their matched normal tissues (2737 samples). We systematically investigated the transcriptomic data to assess the tumour expression profile of 25 known CIFs and their predictive values for patient survival. We used the Xena Functional Genomics tool to analyse the gene expression of CIFs according to neoplastic cellularity in pancreatic adenocarcinoma, which is known to present the highest prevalence of cachexia.

RESULTS

A comprehensive characterization of the expression profiling of secreted genes in different human cancers revealed pathways and mediators with a potential role in cachexia within the tumour microenvironment. Cytokine-related and chemokine-related pathways were enriched in tumour types frequently associated with the syndrome. CIFs presented a tumour-specific expression profile, in which the number of upregulated genes was correlated with the cachexia prevalence (r2 : 0.80; P value: 0.002) and weight loss (r2 : 0.81; P value: 0.002). The distinct gene expression profile, according to tumour type, was significantly associated with prognosis (P value ≤ 1.96 E-06). In pancreatic adenocarcinoma, the upregulated CIF genes were associated with tumours presenting low neoplastic cellularity and high leucocyte fraction and not with tumour grade.

CONCLUSIONS

Our results present a biological dimension of tumour-secreted elements that are potentially useful to explain why specific cancer types are more likely to develop cachexia. The tumour-specific profile of CIFs may help the future development of better targeted therapies to treat cancer types highly associated with the syndrome.

The Secretome Analysis of Activated Human Renal Fibroblasts Revealed Beneficial Effect of the Modulation of the Secreted Peptidyl-Prolyl Cis-Trans Isomerase A in Kidney Fibrosis

The secretome is an important mediator in the permanent process of reciprocity between cells and their environment. Components of secretome are involved in a large number of physiological mechanisms including differentiation, migration, and extracellular matrix modulation. Alteration in secretome composition may therefore trigger cell transformation, inflammation, and diseases. In the kidney, aberrant protein secretion plays a central role in cell activation and transition and in promoting renal fibrosis onset and progression. Using comparative proteomic analyses, we investigated in the present study the impact of cell transition on renal fibroblast cells secretome. Human renal cell lines were stimulated with profibrotic hormones and cytokines, and alterations in secretome were investigated using proteomic approaches. We identified protein signatures specific for the fibrotic phenotype and investigated the impact of modeling secretome proteins on extra cellular matrix accumulation. The secretion of peptidyl-prolyl cis-trans isomerase A (PPIA) was demonstrated to be associated with fibrosis phenotype. We showed that the in-vitro inhibition of PPIA with ciclosporin A (CsA) resulted in downregulation of PPIA and fibronectin (FN1) expression and significantly reduced their secretion. Knockdown studies of PPIA in a three-dimensional (3D) cell culture model significantly impaired the secretion and accumulation of the extracellular matrix (ECM), suggesting a positive therapeutic effect on renal fibrosis progression.

Progresses on bacterial secretomes enlighten research on Mycoplasma secretome

Bacterial secretome is a comprehensive catalog of bacterial proteins that are released or secreted outside the cells. They offer a number of factors that possess several significant roles in virulence as well as cell to cell communication and hence play a core role in bacterial pathogenesis. Sometimes these proteins are bounded with membranes giving them the shape of vesicles called extracellular vesicles (EVs) or outer membrane vesicles (OMVs). Bacteria secrete these proteins via Sec and Tat pathways into the periplasm. Secreted proteins have found to be important as diagnostic markers as well as antigenic factors for the development of an effective candidate vaccine. Recently, the research in the field of secretomics is growing up and getting more interesting due to their direct involvement in the pathogenesis of the microorganisms leading to the infection. Many pathogenic bacteria have been studied for their secretome and the results illustrated novel antigens. This review highlights the secretome studies of different pathogenic bacteria in humans and animals, general secretion mechanisms, different approaches and challenges in the secretome of Mycoplasma sp.

Impaired Airway Epithelial Barrier Integrity in Response to Stenotrophomonas maltophilia Proteases, Novel Insights Using Cystic Fibrosis Bronchial Epithelial Cell Secretomics

Stenotrophomonas maltophilia is a Gram-negative opportunistic pathogen that can chronically colonize the lungs of people with cystic fibrosis (CF) and is associated with lethal pulmonary hemorrhage in immunocompromised patients. Its secreted virulence factors include the extracellular serine proteases StmPR1, StmPR2, and StmPR3. To explore the impact of secreted virulence determinants on pulmonary mucosal defenses in CF, we examined the secretome of human CFBE41o- bronchial epithelial cells in response to treatment with S. maltophilia K279a cell culture supernatant (CS) using a liquid-chromatography-tandem mass spectrometry (LC-MS/MS) based label-free quantitative (LFQ) shotgun proteomics approach for global profiling of the cell secretome. Secretome analysis identified upregulated pathways mainly relating to biological adhesion and epithelial cell signaling in infection, whereas no specific pathways relating to the immune response were enriched. Further exploration of the potentially harmful effects of K279a CS on CF bronchial epithelial cells, demonstrated that K279a CS caused CFBE41o- cell condensation and detachment, reversible by the serine protease inhibitor PMSF. K279a CS also decreased trans-epithelial electrical resistance in CFBE41o- cell monolayers suggestive of disruption of tight junction complexes (TJC). This finding was corroborated by an observed increase in fluorescein isothiocyanate (FITC) dextran permeability and by demonstrating PMSF-sensitive degradation of the tight junction proteins ZO-1 and occludin, but not JAM-A or claudin-1. These observations demonstrating destruction of the CFBE41o- TJC provide a novel insight regarding the virulence of S. maltophilia and may explain the possible injurious effects of this bacterium on the CF bronchial epithelium and the pathogenic mechanism leading to lethal pulmonary hemorrhage.

End-stage renal disease is different from chronic kidney disease in upregulating ROS-modulated proinflammatory secretome in PBMCs - A novel multiple-hit model for disease progression

Background

The molecular mechanisms underlying chronic kidney disease (CKD) transition to end-stage renal disease (ESRD) and CKD acceleration of cardiovascular and other tissue inflammations remain poorly determined.

Methods

We conducted a comprehensive data analyses on 7 microarray datasets in peripheral blood mononuclear cells (PBMCs) from patients with CKD and ESRD from NCBI-GEO databases, where we examined the expressions of 2641 secretome genes (SG).

Results

1) 86.7% middle class (molecular weight >500 Daltons) uremic toxins (UTs) were encoded by SGs; 2) Upregulation of SGs in PBMCs in patients with ESRD (121 SGs) were significantly higher than that of CKD (44 SGs); 3) Transcriptomic analyses of PBMC secretome had advantages to identify more comprehensive secretome than conventional secretomic analyses; 4) ESRD-induced SGs had strong proinflammatory pathways; 5) Proinflammatory cytokines-based UTs such as IL-1β and IL-18 promoted ESRD modulation of SGs; 6) ESRD-upregulated co-stimulation receptors CD48 and CD58 increased secretomic upregulation in the PBMCs, which were magnified enormously in tissues; 7) M1-, and M2-macrophage polarization signals contributed to ESRD- and CKD-upregulated SGs; 8) ESRD- and CKD-upregulated SGs contained senescence-promoting regulators by upregulating proinflammatory IGFBP7 and downregulating anti-inflammatory TGF-β1 and telomere stabilizer SERPINE1/PAI-1; 9) ROS pathways played bigger roles in mediating ESRD-upregulated SGs (11.6%) than that in CKD-upregulated SGs (6.8%), and half of ESRD-upregulated SGs were ROS-independent.

Conclusions

Our analysis suggests novel secretomic upregulation in PBMCs of patients with CKD and ESRD, act synergistically with uremic toxins, to promote inflammation and potential disease progression. Our findings have provided novel insights on PBMC secretome upregulation to promote disease progression and may lead to the identification of new therapeutic targets for novel regimens for CKD, ESRD and their accelerated cardiovascular disease, other inflammations and cancers. (Total words: 279).

Proteomic Analysis of MYB-Regulated Secretome Identifies Functional Pathways and Biomarkers: Potential Pathobiological and Clinical Implications

Earlier we have shown important roles of MYB in pancreatic tumor pathobiology. To better understand the role of MYB in the tumor microenvironment and identify MYB-associated secreted biomarker proteins, we conducted mass spectrometry analysis of the secretome from MYB-modulated and control pancreatic cancer cell lines. We also performed in silico analyses to determine MYB-associated biofunctions, gene networks, and altered biological pathways. Our data demonstrated significant modulation (p < 0.05) of 337 secreted proteins in MYB-silenced MiaPaCa cells, whereas 282 proteins were differentially present in MYB-overexpressing BxPC3 cells, compared to their respective control cells. Alteration of several phenotypes such as cellular movement, cell death and survival, inflammatory response, protein synthesis, etc. was associated with MYB-induced differentially expressed proteins (DEPs) in secretomes. DEPs from MYB-silenced MiaPaCa PC cells were suggestive of the downregulation of genes primarily associated with glucose metabolism, PI3K/AKT signaling, and oxidative stress response, among others. DEPs from MYB-overexpressing BxPC3 cells suggested the enhanced release of proteins associated with glucose metabolism and cellular motility. We also observed that MYB positively regulated the expression of four proteins with potential biomarker properties, i.e., FLNB, ENO1, ITGB1, and INHBA. Mining of publicly available databases using Oncomine and UALCAN demonstrated that these genes are overexpressed in pancreatic tumors and associated with reduced patient survival. Altogether, these data provide novel avenues for future investigations on diverse biological functions of MYB, specifically in the tumor microenvironment, and could also be exploited for biomarker development.

Beyond mass spectrometry, the next step in proteomics

Proteins can be the root cause of a disease, and they can be used to cure it. The need to identify these critical actors was recognized early (1951) by Sanger; the first biopolymer sequenced was a peptide, insulin. With the advent of scalable, single-molecule DNA sequencing, genomics and transcriptomics have since propelled medicine through improved sensitivity and lower costs, but proteomics has lagged behind. Currently, proteomics relies mainly on mass spectrometry (MS), but instead of truly sequencing, it classifies a protein and typically requires about a billion copies of a protein to do it. Here, we offer a survey that illuminates a few alternatives with the brightest prospects for identifying whole proteins and displacing MS for sequencing them. These alternatives all boast sensitivity superior to MS and promise to be scalable and seem to be adaptable to bioinformatics tools for calling the sequence of amino acids that constitute a protein.

Microphysiological sensing platform for an in-situ detection of tissue-secreted cytokines

Understanding the protein-secretion dynamics from single, specific tissues is critical toward the advancement of disease detection and treatments. However, such secretion dynamics remain difficult to measure in vivo due to the uncontrolled contributions from other tissue populations. Here, we describe an integrated platform designed for the reliable, near real-time measurements of cytokines secreted from an in vitro single-tissue model. In our setup, we grow 3D biomimetic tissues to discretize cytokine source, and we separate them from a magnetic microbead-based biosensing system using a Transwell insert. This design integrates physiochemically controlled biological activity, high-sensitivity protein detection (LOD < 20 pg mL-1), and rapid protein diffusion to enable non-invasive, near real-time measurements. To showcase the specificity and sensitivity of the system, we use our setup to probe the inflammatory process related to the protein Interleukine 6 (IL-6) and to the Tumor Necrosis Factor (TNF-α). We show that our setup can monitor the time-dependence profile of IL-6 and TNF-α secretion that results from the electrical and chemical stimulation of 3D skeletal muscle tissues. We demonstrate a novel and affordable methodology for discretizing the secretion kinetics of specific tissues for advancing metabolic-disorder studies and drug-screening applications.

Decoding communication patterns of the innate immune system by quantitative proteomics

The innate immune system is a collective network of cell types involved in cell recruitment and activation using a robust and refined communication system. Engagement of receptor-mediated intracellular signaling initiates communication cascades by conveying information about the host cell status to surrounding cells for surveillance and protection. Comprehensive profiling of innate immune cells is challenging due to low cell numbers, high dynamic range of the cellular proteome, low abundance of secreted proteins, and the release of degradative enzymes (e.g., proteases). However, recent advances in mass spectrometry-based proteomics provides the capability to overcome these limitations through profiling the dynamics of cellular processes, signaling cascades, post-translational modifications, and interaction networks. Moreover, integration of technologies and molecular datasets provide a holistic view of a complex and intricate network of communications underscoring host defense and tissue homeostasis mechanisms. In this Review, we explore the diverse applications of mass spectrometry-based proteomics in innate immunity to define communication patterns of the innate immune cells during health and disease. We also provide a technical overview of mass spectrometry-based proteomic workflows, with a focus on bottom-up approaches, and we present the emerging role of proteomics in immune-based drug discovery while providing a perspective on new applications in the future.

Cellular Interactions in the Tumor Microenvironment: The Role of Secretome

Over the past years, it has become evident that cancer initiation and progression depends on several components of the tumor microenvironment, including inflammatory and immune cells, fibroblasts, endothelial cells, adipocytes, and extracellular matrix. These components of the tumor microenvironment and the neoplastic cells interact with each other providing pro and antitumor signals. The tumor-stroma communication occurs directly between cells or via a variety of molecules secreted, such as growth factors, cytokines, chemokines and microRNAs. This secretome, which derives not only from tumor cells but also from cancer-associated stromal cells, is an important source of key regulators of the tumorigenic process. Their screening and characterization could provide useful biomarkers to improve cancer diagnosis, prognosis, and monitoring of treatment responses.

A gene expression network analysis of the pancreatic islets from lean and obese mice identifies complement 1q like-3 secreted protein as a regulator of β-cell function

Secreted proteins are important metabolic regulators. Identifying and characterizing the role of secreted proteins from small tissue depots such as islets of Langerhans, which are required for the proper control of whole-body energy metabolism, remains challenging. Our objective was to identify islet-derived secreted proteins that affect islet function in obesity. Lean and obese mouse islet expression data were analyzed by weighted gene co-expression network analysis (WGCNA) to identify trait-associated modules. Subsequently, genes within these modules were filtered for transcripts that encode for secreted proteins based on intramodular connectivity, module membership, and differential expression. Complement 1q like-3 (C1ql3) secreted protein was identified as a hub gene affecting islet function in obesity. Co-expression network, hierarchal clustering, and gene-ontology based approaches identified a putative role for C1ql3 in regulating β-cell insulin secretion. Biological validation shows that C1ql3 is expressed in β-cells, it inhibits insulin secretion and key genes that are involved in β-cell function. Moreover, the increased expression of C1ql3 is correlated with the reduced insulin secretion in islets of obese mice. Herein, we demonstrate a streamlined approach to effectively screen and determine the function of secreted proteins in islets, and identified C1ql3 as a putative contributor to reduced insulin secretion in obesity, linking C1ql3 to an increased susceptibility to type 2 diabetes.

Metabolomics Analysis of Mesenchymal Stem Cells

Various mesenchymal stem cells as easily accessible and multipotent cells can share different essential signaling pathways related to their stemness ability. Understanding the mechanism of stemness ability can be useful for controlling the stem cells for regenerative medicine targets. In this context, OMICs studies can analyze the mechanism of different stem cell properties or stemness ability via a broad range of current high-throughput techniques. This field is fundamentally directed toward the analysis of whole genome (genomics), mRNAs (transcriptomics), proteins (proteomics) and metabolites (metabolomics) in biological samples. According to several studies, metabolomics is more effective than other OMICs ّfor various system biology concerns. Metabolomics can elucidate the biological mechanisms of various mesenchymal stem cell function by measuring their metabolites such as their secretome components. Analyzing the metabolic alteration of mesenchymal stem cells can be useful to promote their regenerative medicine application.

Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

Most patients with locally advanced rectal cancer (LARC) present incomplete pathological response (pIR) to neoadjuvant chemoradiotherapy (nCRT). Despite the efforts to predict treatment response using tumor-molecular features, as differentially expressed genes, no molecule has proved to be a strong biomarker. The tumor secretome analysis is a promising strategy for biomarkers identification, which can be assessed using transcriptomic data. We performed transcriptomic-based secretome analysis to select potentially secreted proteins using an in silico approach. The tumor expression profile of 28 LARC biopsies collected before nCRT was compared with normal rectal tissues (NT). The expression profile showed no significant differences between complete (pCR) and incomplete responders to nCRT. Genes with increased expression (pCR = 106 and pIR = 357) were used for secretome analysis based on public databases (Vesiclepedia, Human Cancer Secretome, and Plasma Proteome). Seventeen potentially secreted candidates (pCR = 1, pIR = 13 and 3 in both groups) were further investigated in two independent datasets (TCGA and GSE68204) confirming their over-expression in LARC and association with nCRT response (GSE68204). The expression of circulating amphiregulin and cMET proteins was confirmed in serum from 14 LARC patients. Future studies in liquid biopsies could confirm the utility of these proteins for personalized treatment in LARC patients.

Systems-based approaches for investigation of inter-tissue communication

Secreted proteins serve as crucial mediators of many physiology processes, and beginning with the discovery of insulin, studies have revealed numerous context-specific regulatory networks across various cell types. Here, we review “omics” approaches to deconvolute the complex milieu of proteins that are released from the cell. We emphasize a novel “systems genetics” approach our laboratory has developed to investigate mechanisms of tissue-tissue communication using population-based datasets. Finally, we highlight potential future directions for these studies, discuss several caveats, and propose new ways to investigate modes of endocrine communication.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

Addressing the Manufacturing Challenges of Cell-Based Therapies

Exciting developments in the cell therapy field over the last decades have led to an increasing number of clinical trials and the first cell products receiving marketing authorization. In spite of substantial progress in the field, manufacturing of cell-based therapies presents multiple challenges that need to be addressed in order to assure the development of safe, efficacious, and cost-effective cell therapies.The manufacturing process of cell-based therapies generally requires tissue collection, cell isolation, culture and expansion (upstream processing), cell harvest, separation and purification (downstream processing), and, finally, product formulation and storage. Each one of these stages presents significant challenges that have been the focus of study over the years, leading to innovative and groundbreaking technological advances, as discussed throughout this chapter.Delivery of cell-based therapies relies on defining product targets while controlling process variable impact on cellular features. Moreover, commercial viability is a critical issue that has had damaging consequences for some therapies. Implementation of cost-effectiveness measures facilitates healthy process development, potentially being able to influence end product pricing.Although cell-based therapies represent a new level in bioprocessing complexity in every manufacturing stage, they also show unprecedented levels of therapeutic potential, already radically changing the landscape of medical care.

Quantifying single-cell secretion in real time using resonant hyperspectral imaging

Cell communication is primarily regulated by secreted proteins, whose inhomogeneous secretion often indicates physiological disorder. Parallel monitoring of innate protein-secretion kinetics from individual cells is thus crucial to unravel systemic malfunctions. Here, we report a label-free, high-throughput method for parallel, in vitro, and real-time analysis of specific single-cell signaling using hyperspectral photonic crystal resonant technology. Heterogeneity in physiological thrombopoietin expression from individual HepG2 liver cells in response to platelet desialylation was quantified demonstrating how mapping real-time protein secretion can provide a simple, yet powerful approach for studying complex physiological systems regulating protein production at single-cell resolution.

Intestinal in vitro and ex vivo Models to Study Host-Microbiome Interactions and Acute Stressors

The gut microbiome is extremely important for maintaining homeostasis with host intestinal epithelial, neuronal, and immune cells and this host-microbe interaction is critical during times of stress or disease. Environmental, nutritional, and cognitive stress are just a few factors known to influence the gut microbiota and are thought to induce microbial dysbiosis. Research on this bidirectional relationship as it pertains to health and disease is extensive and rapidly expanding in both in vivo and in vitro/ex vivo models. However, far less work has been devoted to studying effects of host-microbe interactions on acute stressors and performance, the underlying mechanisms, and the modulatory effects of different stressors on both the host and the microbiome. Additionally, the use of in vitro/ex vivo models to study the gut microbiome and human performance has not been researched extensively nor reviewed. Therefore, this review aims to examine current evidence concerning the current status of in vitro and ex vivo host models, the impact of acute stressors on gut physiology/microbiota as well as potential impacts on human performance and how we can parlay this information for DoD relevance as well as the broader scientific community. Models reviewed include widely utilized intestinal cell models from human and animal models that have been applied in the past for stress or microbiology research as well as ex vivo organ/tissue culture models and new innovative models including organ-on-a-chip and co-culture models.

A proteomic signature that reflects pancreatic beta-cell function

AIM

Proteomics has the potential to enhance early identification of beta-cell dysfunction, in conjunction with monitoring the various stages of type 2 diabetes onset. The most routine method of assessing pancreatic beta-cell function is an oral glucose tolerance test, however this method is time consuming and carries a participant burden. The objectives of this research were to identify protein signatures and pathways related to pancreatic beta-cell function in fasting blood samples.

METHODS

Beta-cell function measures were calculated for MECHE study participants who completed an oral glucose tolerance test and had proteomic data (n = 100). Information on 1,129 protein levels was obtained using the SOMAscan assay. Receiver operating characteristic curves were used to assess discriminatory ability of proteins of interest. Subsequent in vitro experiments were performed using the BRIN-BD11 pancreatic beta-cell line. Replication of findings were achieved in a second human cohort where possible.

RESULTS

Twenty-two proteins measured by aptamer technology were significantly associated with beta-cell function/HOMA-IR while 17 proteins were significantly associated with the disposition index (p ≤ 0.01). Receiver operator characteristic curves determined the protein panels to have excellent discrimination between low and high beta-cell function. Linear regression analysis determined that beta-endorphin and IL-17F have strong associations with beta-cell function/HOMA-IR, β = 0.039 (p = 0.005) and β = -0.027 (p = 0.013) respectively. Calcineurin and CRTAM were strongly associated with the disposition index (β = 0.005 and β = 0.005 respectively, p = 0.012). In vitro experiments confirmed that IL-17F modulated insulin secretion in the BRIN-BD11 cell line, with the lower concentration of 10 ng/mL significantly increasing glucose stimulated insulin secretion (p = 0.043).

CONCLUSIONS

Early detection of compromised beta-cell function could allow for implementation of nutritional and lifestyle interventions before progression to type 2 diabetes.

Method for Dynamically Detecting Secretions from Single Cells Using a Nanopore

Secreted proteins mediate cell-to-cell communications. Thus, eavesdropping on the secretome could reveal the cellular phenotype, but it is challenging to detect the proteins because they are secreted only in minute amounts and then diluted in blood plasma or contaminated by cell culture medium or the lysate. In this pilot study, it is demonstrated that secretions from single cancer cells can be detected and dynamically analyzed through measurements of blockades in the electrolytic current due to single molecules translocating through a nanopore in a thin inorganic membrane. It is established that the distribution of blockades can be used to differentiate three different cancer cell lines (U937, MDA-MB-231, and MCF-7) in real time and quickly (<20 s). Importantly, the distinctive blockades associated with the chemokine CCL5, a prognostic factor for disease progression in breast cancer, along with other low-mass biomarkers of breast cancer (PI3, TIMP1, and MMP1) were identified in the context of the secretome of these three cell types, tracked with time, and used to provide information on the cellular phenotype.

Robust signal peptides for protein secretion in Yarrowia lipolytica: identification and characterization of novel secretory tags

Upon expression of a given protein in an expression host, its secretion into the culture medium or cell-surface display is frequently advantageous in both research and industrial contexts. Hence, engineering strategies targeting folding, trafficking, and secretion of the proteins gain considerable interest. Yarrowia lipolytica has emerged as an efficient protein expression platform, repeatedly proved to be a competitive secretor of proteins. Although the key role of signal peptides (SPs) in secretory overexpression of proteins and their direct effect on the final protein titers are widely known, the number of reports on manipulation with SPs in Y. lipolytica is rather scattered. In this study, we assessed the potential of ten different SPs for secretion of two heterologous proteins in Y. lipolytica. Genomic and transcriptomic data mining allowed us to select five novel, previously undescribed SPs for recombinant protein secretion in Y. lipolytica. Their secretory potential was assessed in comparison with known, widely exploited SPs. We took advantage of Golden Gate approach, for construction of expression cassettes, and micro-volume enzymatic assays, for functional screening of large libraries of recombinant strains. Based on the adopted strategy, we identified novel secretory tags, characterized their secretory capacity, indicated the most potent SPs, and suggested a consensus sequence of a potentially robust synthetic SP to expand the molecular toolbox for engineering Y. lipolytica.