Transglutaminase-2 (TG2) is the most highly and ubiquitously expressed member of the transglutaminase enzyme family and is primarily involved in protein cross-linking. TG2 has been implicated in the development and progression of numerous cancers, with a direct role in multiple cellular processes and pathways linked to apoptosis, chemoresistance, epithelial-mesenchymal transition, and stem cell phenotype. The tumour microenvironment (TME) is critical in the formation, progression, and eventual metastasis of cancer, and increasing evidence points to a role for TG2 in matrix remodelling, modulation of biomechanical properties, cell adhesion, motility, and invasion. There is growing interest in targeting the TME therapeutically in response to advances in the understanding of its critical role in disease progression, and a number of approaches targeting biophysical properties and biomechanical signalling are beginning to show clinical promise. In this review we aim to highlight the wide array of processes in which TG2 influences the TME, focussing on its potential role in the dynamic tissue remodelling and biomechanical events increasingly linked to invasive and aggressive behaviour. Drug development efforts have yielded a range of TG2 inhibitors, and ongoing clinical trials may inform strategies for targeting the biomolecular and biomechanical function of TG2 in the TME.

Single particle characterization has become increasingly relevant for research into extracellular vesicles, progressing from bulk analysis techniques and first-generation particle analysis to comprehensive multi-parameter measurements such as nano-flow cytometry (nFCM). nFCM is a form of flow cytometry that utilizes instrumentation specifically designed for nano-particle analysis, allowing for thousands of EVs to be characterized per minute both with and without the use of staining techniques.High resolution side scatter (SS) detection allows for size and concentration to be determined for all biological particles larger than 45 nm, while simultaneous fluorescence (FL) detection identifies the presence of labeled markers and targets of interest. Labeled subpopulations can then be described in quantitative units of particles/mL or as a percentage of the total particles identified by side scatter.Here, EVs derived from conditioned cell culture media (CCM) are labeled with both a lipid dye, to identify particles with a membrane, and antibodies specific for CD9, CD63, and CD81 as common EV markers. Measurements of comparison material, a concentration standard and a size standard of silica nanospheres, as well as labeled sample material are analyzed in a 1-minute analysis. The software is then used to measure the concentration and size distribution profile of all particles, independent of labeling, before determining the particles that are positive for each of the labels.Simultaneous SS and FL detection can be utilized flexibly with many different EV sources and labeling targets, both external and internal, describing EV samples in a comprehensive and quantitative manner.

Single particle characterization has become increasingly relevant for research into extracellular vesicles, progressing from bulk analysis techniques and first-generation particle analysis to comprehensive multi-parameter measurements such as nano-flow cytometry (nFCM). nFCM is a form of flow cytometry that utilizes instrumentation specifically designed for nano-particle analysis, allowing for thousands of EVs to be characterized per minute both with and without the use of staining techniques.High resolution side scatter (SS) detection allows for size and concentration to be determined for all biological particles larger than 45 nm, while simultaneous fluorescence (FL) detection identifies the presence of labeled markers and targets of interest. Labeled subpopulations can then be described in quantitative units of particles/mL or as a percentage of the total particles identified by side scatter.Here, EVs derived from conditioned cell culture media (CCM) are labeled with both a lipid dye, to identify particles with a membrane, and antibodies specific for CD9, CD63, and CD81 as common EV markers. Measurements of comparison material, a concentration standard and a size standard of silica nanospheres, as well as labeled sample material are analyzed in a 1-minute analysis. The software is then used to measure the concentration and size distribution profile of all particles, independent of labeling, before determining the particles that are positive for each of the labels.Simultaneous SS and FL detection can be utilized flexibly with many different EV sources and labeling targets, both external and internal, describing EV samples in a comprehensive and quantitative manner.

The proteomic profile of extracellular vesicles (EVs) from cerebrospinal fluid (CSF) can reveal novel biomarkers for diseases of the brain. Here, we validate an ultrafiltration combined with size-exclusion chromatography (UF-SEC) method for isolation of EVs from canine CSF and probe the effect of starting volume on the EV proteomics profile. First, we performed a literature review of CSF EV articles to define the current state of art, discovering a need for basic characterisation of CSF EVs. Secondly, we isolated EVs from CSF by UF-SEC and characterised the SEC fractions by protein amount, particle count, transmission electron microscopy, and immunoblotting. Data are presented as mean ± standard deviation. Using proteomics, SEC fractions 3–5 were compared and enrichment of EV markers in fraction 3 was detected, whereas fractions 4–5 contained more apolipoproteins. Lastly, we compared starting volumes of pooled CSF (6 ml, 3 ml, 1 ml, and 0.5 ml) to evaluate the effect on the proteomic profile. Even with a 0.5 ml starting volume, 743 ± 77 or 345 ± 88 proteins were identified depending on whether ‘matches between runs’ was active in MaxQuant. The results confirm that UF-SEC effectively isolates CSF EVs and that EV proteomic analysis can be performed from 0.5 ml of canine CSF.

The proteomic profile of extracellular vesicles (EVs) from cerebrospinal fluid (CSF) can reveal novel biomarkers for diseases of the brain. Here, we validate an ultrafiltration combined with size-exclusion chromatography (UF-SEC) method for isolation of EVs from canine CSF and probe the effect of starting volume on the EV proteomics profile. First, we performed a literature review of CSF EV articles to define the current state of art, discovering a need for basic characterisation of CSF EVs. Secondly, we isolated EVs from CSF by UF-SEC and characterised the SEC fractions by protein amount, particle count, transmission electron microscopy, and immunoblotting. Data are presented as mean ± standard deviation. Using proteomics, SEC fractions 3-5 were compared and enrichment of EV markers in fraction 3 was detected, whereas fractions 4-5 contained more apolipoproteins. Lastly, we compared starting volumes of pooled CSF (6ml, 3ml, 1ml, and 0.5ml) to evaluate the effect on the proteomic profile. Even with a 0.5ml starting volume, 743±77 or 345±88 proteins were identified depending on whether 'matches between runs' was active in MaxQuant. The results confirm that UF-SEC effectively isolates CSF EVs and that EV proteomic analysis can be performed from 0.5ml of canine CSF.