Cathelicidin-3 Associated With Serum Extracellular Vesicles Enables Early Diagnosis of a Transmissible Cancer

Coevolution promotes the coexistence of Tasmanian devils and a fatal, transmissible cancer

Emerging infectious diseases threaten natural populations, and data-driven modeling is critical for predicting population dynamics. Despite the importance of integrating ecology and evolution in models of host-pathogen dynamics, there are few wild populations for which long-term ecological datasets have been coupled with genome-scale data. Tasmanian devil (Sarcophilus harrisii) populations have declined range wide due to devil facial tumor disease (DFTD), a fatal transmissible cancer. Although early ecological models predicted imminent devil extinction, diseased devil populations persist at low densities, and recent ecological models predict long-term devil persistence. Substantial evidence supports the evolution of both devils and DFTD, suggesting coevolution may also influence continued devil persistence. Thus, we developed an individual-based, eco-evolutionary model of devil-DFTD coevolution parameterized with nearly 2 decades of devil demography, DFTD epidemiology, and genome-wide association studies. We characterized potential devil-DFTD coevolutionary outcomes and predicted the effects of coevolution on devil persistence and devil-DFTD coexistence. We found a high probability of devil persistence over 50 devil generations (100 years) and a higher likelihood of devil-DFTD coexistence, with greater devil recovery than predicted by previous ecological models. These novel results add to growing evidence for long-term devil persistence and highlight the importance of eco-evolutionary modeling for emerging infectious diseases.

Extracellular vesicles: an emerging tool for wild immunology

The immune system is crucial for defending organisms against pathogens and maintaining health. Traditionally, research in immunology has relied on laboratory animals to understand how the immune system works. However, there is increasing recognition that wild animals, due to their greater genetic diversity, lifespan, and environmental exposures, have much to contribute to basic and translational immunology. Unfortunately, logistical challenges associated with collecting and storing samples from wildlife, and the lack of commercially available species-specific reagents have hindered the advancement of immunological research on wild species. Extracellular vesicles (EVs) are cell-derived nanoparticles present in all body fluids and tissues of organisms spanning from bacteria to mammals. Human and lab animal studies indicate that EVs are involved in a range of immunological processes, and recent work shows that EVs may play similar roles in diverse wildlife species. Thus, EVs can expand the toolbox available for wild immunology research, helping to overcome some of the challenges associated with this work. In this paper, we explore the potential application of EVs to wild immunology. First, we review current understanding of EV biology across diverse organisms. Next, we discuss key insights into the immune system gained from research on EVs in human and laboratory animal models and highlight emerging evidence from wild species. Finally, we identify research themes in wild immunology that can immediately benefit from the study of EVs and describe practical considerations for using EVs in wildlife research.

Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum

Extracellular vesicles (EVs) are important players in melanoma progression, but their use as clinical biomarkers has been limited by the difficulty of profiling blood-derived EV proteins with high depth of coverage, the requirement for large input amounts, and complex protocols. Here, we provide a streamlined and reproducible experimental workflow to identify plasma- and serum- derived EV proteins of healthy donors and melanoma patients using minimal amounts of sample input. SEC-DIA-MS couples size-exclusion chromatography to EV concentration and deep-proteomic profiling using data-independent acquisition. From as little as 200 µL of plasma per patient in a cohort of three healthy donors and six melanoma patients, we identified and quantified 2896 EV-associated proteins, achieving a 3.5-fold increase in depth compared to previously published melanoma studies. To compare the EV-proteome to unenriched blood, we employed an automated workflow to deplete the 14 most abundant proteins from plasma and serum and thereby approximately doubled protein group identifications versus native blood. The EV proteome diverged from corresponding unenriched plasma and serum, and unlike the latter, separated healthy donor and melanoma patient samples. Furthermore, known melanoma markers, such as MCAM, TNC, and TGFBI, were upregulated in melanoma EVs but not in depleted melanoma plasma, highlighting the specific information contained in EVs. Overall, EVs were significantly enriched in intact membrane proteins and proteins related to SNARE protein interactions and T-cell biology. Taken together, we demonstrated the increased sensitivity of an EV-based proteomic workflow that can be easily applied to larger melanoma cohorts and other indications.

Liver-derived extracellular vesicles improve whole-body glycaemic control via inter-organ communication

Small extracellular vesicles (EVs) are signalling messengers that regulate inter-tissue communication through delivery of their molecular cargo. Here, we show that liver-derived EVs are acute regulators of whole-body glycaemic control in mice. Liver EV secretion into the circulation is increased in response to hyperglycaemia, resulting in increased glucose effectiveness and insulin secretion through direct inter-organ EV signalling to skeletal muscle and the pancreas, respectively. This acute blood glucose lowering effect occurs in healthy and obese mice with non-alcoholic fatty liver disease, despite marked remodelling of the liver-derived EV proteome in obese mice. The EV-mediated blood glucose lowering effects were recapitulated by administration of liver EVs derived from humans with or without progressive non-alcoholic fatty liver disease, suggesting broad functional conservation of liver EV signalling and potential therapeutic utility. Taken together, this work reveals a mechanism whereby liver EVs act on peripheral tissues via endocrine signalling to restore euglycaemia in the postprandial state.

Early Cancer Biomarker Discovery Using DIA-MS Proteomic Analysis of EVs from Peripheral Blood

One of the cornerstones of effective cancer treatment is early diagnosis. In this context, the identification of proteins that can serve as cancer biomarkers in bodily fluids ("liquid biopsies") has gained attention over the last decade. Plasma and serum fractions of blood are the most commonly investigated sources of potential cancer liquid biopsy biomarkers. However, the high complexity and dynamic range typical of these fluids hinders the sensitivity of protein detection by the most commonly used mass spectrometry technology (data-dependent acquisition mass spectrometry (DDA-MS)). Recently, data-independent acquisition mass spectrometry (DIA-MS) techniques have overcome the limitations of DDA-MS, increasing sensitivity and proteome coverage. In addition to DIA-MS, isolating extracellular vesicles (EVs) can help to increase the depth of serum/plasma proteome coverage by improving the identification of low-abundance proteins which are a potential treasure trove of diagnostic molecules. EVs, the nano-sized membrane-enclosed vesicles present in most bodily fluids, contain proteins which may serve as potential biomarkers for various cancers. Here, we describe a detailed protocol that combines DIA-MS and EV methodologies for discovering and validating early cancer biomarkers using blood serum. The pipeline includes size exclusion chromatography methods to isolate serum-derived extracellular vesicles and subsequent EV sample preparation for liquid chromatography and mass spectrometry analysis. Procedures for spectral library generation by DDA-MS incorporate methods for off-line peptide separation by microflow HPLC with automated fraction concatenation. Analysis of the samples by DIA-MS includes recommended protocols for data processing and statistical methods. This pipeline will provide a guide to discovering and validating EV-associated proteins that can serve as sensitive and specific biomarkers for early cancer detection and other diseases.