Kinetics and interaction studies of anti-tetraspanin antibodies and ICAM-1 with extracellular vesicle subpopulations using continuous flow quartz crystal microbalance biosensor

Continuous flow quartz crystal microbalance (QCM) was utilized to study binding kinetics between EV subpopulations (exomere- and exosome-sized EVs) and four affinity ligands: monoclonal antibodies against tetraspanins (anti-CD9, anti-CD63, and anti-CD81) and recombinant intercellular adhesion molecule-1 (ICAM-1) or CD54 protein). High purity CD9+, CD63+, and CD81+ EV subpopulations of <50 nm exomeres and 50-80 nm exosomes were isolated and fractionated using our recently developed on-line coupled immunoaffinity chromatography - asymmetric flow field-flow fractionation system. Adaptive Interaction Distribution Algorithm (AIDA), specifically designed for the analysis of complex biological interactions, was used with a four-step procedure for reliable estimation of the degree of heterogeneity in rate constant distributions. Interactions between exomere-sized EVs and anti-tetraspanin antibodies demonstrated two interaction sites with comparable binding kinetics and estimated dissociation constants Kd ranging from nM to fM. Exomeres exhibited slightly higher affinity compared to exosomes. The highest affinity with anti-tetraspanin antibodies was achieved with CD63+ EVs. The interaction of EV subpopulations with ICAM-1 involved in cell internalization of EVs was also investigated. EV - ICAM-1 interaction was also of high affinity (nM to pM range) with overall lower affinity compared to the interactions of anti-tetraspanin antibodies and EVs. Our findings proved that QCM is a valuable label-free tool for kinetic studies with limited sample concentration, and that advanced algorithms, such as AIDA, are crucial for proper determination of kinetic heterogeneity. To the best of our knowledge, this is the first kinetic study on the interaction between plasma-derived EV subpopulations and anti-tetraspanin antibodies and ICAM-1.Peer reviewe

Raman spectroscopy combined with comprehensive gas chromatography for label-free characterization of plasma-derived extracellular vesicle subpopulations

Raman spectroscopy together with comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GCxGC-TOFMS) was employed to characterize exomere- (<50 nm) and exosome-sized (50-80 nm) EVs isolated from human plasma by the novel on-line immunoaffinity chromatography - asymmetric flow field-flow fractionation method. CD9(+), CD63(+), and CD81(+) EVs were selected to represent general EV subpopulations secreted into plasma, while CD61(+) EVs represented the specific EV subset derived from platelets. Raman spectroscopy could distinguish EVs from non-EV particles, including apolipoprotein B-100-containing lipoproteins, signifying its potential in EV purity assessment. Moreover, platelet-derived (CD61(+)) EVs of both exomere and exosome sizes were discriminated from other EV subpopulations due to different biochemical compositions. Further investigations demonstrated composition differences between exomere- and exosome-sized EVs, confirming the applicability of Raman spectroscopy in distinguishing EVs, not only from different origins but also sizes. In addition, fatty acids that act as building blocks for lipids and membranes in EVs were studied by GCxGC-TOF-MS. The results achieved highlighted differences in EV fatty acid compositions in both esterified (membrane lipids) and non-esterified (free fatty acids) fractions, indicating possible differences in membrane structures, biological functions, and roles in cell-to-cell communications of EV subpopulations.Peer reviewe

Reliable Strategy for Analysis of Complex Biosensor Data

When using biosensors, analyte biomolecules of several different concentrations are percolated over a chip with immobilized ligand molecules that form complexes with analytes. However, in many cases of biological interest, e.g., in antibody interactions, complex formation steady-state is not reached. The data measured are so-called sensorgram, one for each analyte concentration, with total complex concentration vs time. Here we present a new four-step strategy for more reliable processing of this complex kinetic binding data and compare it with the standard global fitting procedure. In our strategy, we first calculate a dissociation graph to reveal if there are any heterogeneous interactions. Thereafter, a new numerical algorithm, AIDA, is used to get the number of different complex formation reactions for each analyte concentration level. This information is then used to estimate the corresponding complex formation rate constants by fitting to the measured sensorgram one by one. Finally, all estimated rate constants are plotted and clustered, where each cluster represents a complex formation. Synthetic and experimental data obtained from three different QCM biosensor experimental systems having fast (close to steady-state), moderate, and slow kinetics (far from steady-state) were evaluated using the four-step strategy and standard global fitting. The new strategy allowed us to more reliably estimate the number of different complex formations, especially for cases of complex and slow dissociation kinetics. Moreover, the new strategy proved to be more robust as it enables one to handle system drift, i.e., data from biosensor chips that deteriorate over time.Peer reviewe

Determination of free amino acids, saccharides, and selected microbes in biogenic atmospheric aerosols - seasonal variations, particle size distribution, chemical and microbial relations.

Primary biological aerosol particles (PBAPs) play an important role in the interaction between biosphere, atmosphere, and climate, affecting cloud and precipitation formation processes. The presence of pollen, plant fragments, spores, bacteria, algae, and viruses in PBAPs is well known. In order to explore the complex interrelationships between airborne and particulate chemical tracers (amino acids, saccharides), gene copy numbers (16S and 18S for bacteria and fungi, respectively), gas phase chemistry, and the particle size distribution, 84 size-segregated aerosol samples from four particle size fractions ( 10 mu m) were collected at the SMEAR II station, Finland, in autumn 2017. The gene copy numbers and size distributions of bacteria, Pseudomonas, and fungi in biogenic aerosols were determined by DNA extraction and amplification. In addition, free amino acids (19) and saccharides (8) were analysed in aerosol samples by hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS). Different machine learning (ML) approaches, such as cluster analysis, discriminant analysis, neural network analysis, and multiple linear regression (MLR), were used for the clarification of several aspects related to the composition of biogenic aerosols. Clear variations in composition as a function of the particle size were observed. In most cases, the highest concentration values and gene copy numbers (in the case of microbes) were observed for 2.5-10 mu m particles, followed by > 10, 1-2.5, and < 1.0 mu m particles. In addition, different variables related to the air and soil temperature, the UV radiation, and the amount of water in the soil affected the composition of biogenic aerosols. In terms of interpreting the results, MLR provided the greatest improvement over classical statistical approaches such as Pearson correlation among the ML approaches considered. In all cases, the explained variance was over 91 %. The great variability of the samples hindered the clarification of common patterns when evaluating the relation between the presence of microbes and the chemical composition of biogenic aerosols. Finally, positive correlations were observed between gas-phase VOCs (such as acetone, toluene, methanol, and 2-methyl-3-buten-2-ol) and the gene copy numbers of microbes in biogenic aerosols.Peer reviewe

Elucidation of Molecular Properties and Interactions of Nanosized Biomacromolecules

This doctoral dissertation focuses on the elucidation of biochemical and chemical compositions of clinically relevant human plasma-derived nanosized particles, namely lipoproteins and extracellular vesicle subpopulations (EVs) isolated by on-line coupled immunoaffinity – asymmetric flow field-flow fractionation. Raman spectroscopy and chromatographic techniques along with statistical and computational models for complex data analysis were employed for compositional studies. Continuous flow quartz crystal microbalance (QCM) combined with an advanced numerical tool namely Adaptive Interaction Distribution Algorithm or AIDA gave valuable information on their binding kinetics and interactions, also helpful for the development of the isolation methods. The first step was to develop a fast and reliable platform for the isolation and fractionation of low-density lipoprotein (LDL) particles and EV subpopulations from human plasma. The isolation was based on the highly specific and selective affinity chromatography with monolithic disk columns, enabling convective mass transport and high permeability. The LDL isolation system utilized two monolithic disk columns, one immobilized with chondroitin-6-sulfate (C6S) and another with monoclonal anti-apolipoprotein B-100 (anti-apoB-100) antibody. The first disk removed very-low-density and intermediate-density lipoproteins from human plasma, while the second isolated LDLs from the flow-through plasma. EV isolation methods included four immunoaffinity ligands, monoclonal anti-CD9, anti-CD63, anti-CD81, and anti-CD61 antibodies. The isolates were further on-line fractionated by asymmetric flow field-flow fractionation, resulting in EV subpopulations with size ranges of < 50 nm exomeres and 50-120 nm exosomes. The developed systems allowed automated, quick, highly reliable, and successful isolation and fractionation of both lipoproteins and EV subpopulations with minimal losses and contamination. Raman spectroscopy combined with statistical models was successfully used to prove the hypothesis that plasma-derived EVs of different sizes and origins have different biochemical compositions. In addition, EVs were clearly distinguished from non-EV components, such as apoB-100-containing lipoproteins and human plasma. Plasma-derived EV subpopulations, including CD9+, CD63+, and CD81+ EVs, gave distinct spectral compositions compared to platelet-derived CD61+ EV subpopulations, and the diversity was even found within exomere and exosome size ranges. In parallel, the fatty acid composition of lipoproteins and EV subpopulations was analyzed by comprehensive two-dimensional gas chromatography – time-of-flight mass spectrometry and the amino acid and glucose content by hydrophilic interaction liquid chromatography – tandem mass spectrometry. EV subpopulations were free from detectable apoB-100-containing lipoproteins and differed in amino acid and fatty acid compositions. Detailed binding kinetics and interactions carried out by continuous flow QCM and data analysis tool AIDA gave knowledge of biological system heterogeneity and binding kinetics parameters, useful for the development of affinity chromatographic methods and for the determination of molecular properties of both lipoproteins and EV subpopulations.Väitöskirjassa selvitetään useilla eri menetelmillä kliinisesti merkityksellisten, ihmisen plasmaperäisten nanokokoisten hiukkasten, kuten lipoproteiinien ja solunulkoisten vesikkelialapopulaatioiden (EV), biokemiallista ja kemiallista koostumusta. Hiukkaset eristettiin analyyttisen kemian laboratoriossa kehitetyllä, automatisoidulla menetelmällä, jossa kaksi erotustekniikkaa, immunoaffiniteettikromatografia ja poikittaisvirtauskenttävirtausfraktiointi oli liitetty yhteen. Hiukkasten koostumusta tutkittiin Ramanspektroskopialla, kromatografisin tekniikoin ja hyödyntäen tilastollisia ja laskennallisia malleja. Kvartsikidemikrovaaka yhdistettynä edistyneeseen numeeriseen työkaluun nimeltään ”Adaptive Interaction Distribution Algorithm” antoi yksityiskohtaisempaa tietoa nanokokoisten hiukkasten sitoutumiskinetiikasta ja vuorovaikutuksista. Tätä tietoa hyödynnettiin myös hiukkasten eristysmenetelmien kehittämisessä. Uudessa, vain pieniä näytemääriä tarvitsevassa alhaisen tiheyden lipoproteiinihiukkasten (LDL) nopeassa ja selektiivisessä eristysmenetelmässä ihmisen plasmasta käytettiin kahta peräkkäistä monoliittista kiekkomaista kolonnia, joista ensimmäiseen oli sidottu kondroitiini-6-sulfaattia ja toiseen monoklonaalista anti-apoB-100 vasta-ainetta. EV-partikkeleiden eristämisessä taas käytettiin neljää em. monoliittista kolonnia, joihin oli sidottu erilaisia, tarkoin valittuja immunoaffiniteettiligandeja. Eristetyt EV-hiukkaset fraktioitiin edelleen menetelmään suoraan liitetyllä poikittaisvirtauskenttävirtausfraktioinnilla EV-alaryhmiin, joiden kokojakauma-alueet olivat < 50 nm (eksomeerit) ja 50–120 nm (eksosomit). Hiukkasten rasvahappokoostumusta tutkittiin laajalla kaksidimensionaalisella kaasukromatografialla ja aminohappo- sekä glukoosipitoisuuksia hydrofiilisellä vuorovaikutusnestekromatografialla. Ramanspektroskopiatutkimuksissa hyödynnettiin myös tilastollisia malleja, joiden avulla onnistuttiin todistamaan hypoteesi, että eri kokoluokan ja alkuperän EV-hiukkasilla on erilaiset biokemialliset koostumukset. Lisäksi suoraliitäntämenetelmällä eristetyt EV-hiukkaset saatiin selvästi eroteltua plasman muista hiukkasista, kuten esimerkiksi lipoproteiineista, jotka ovat usein epäpuhtauksina perinteisillä eristysmenetelmillä eristetyissä näytteissä. Lisäksi käytetyllä suoraliitäntämenetelmällä eristetyt EV-hiukkaset saatiin luotettavasti eroteltua plasman muista hiukkasista, kuten esimerkiksi lipoproteiineista, jotka ovat usein epäpuhtauksina perinteisillä eristysmenetelmillä eristetyissä näytteiss

Affinity monolith chromatography in the isolation and separation of biomacromolecules

The literature part of this thesis contains the review of affinity chromatography using monolithic stationary supports in the separation and isolation of biomacromolecules, a technique known as affinity monolith chromatography (AMC). Affinity chromatography is a liquid separation technique operating on the principle of reversible binding of affinity ligands and target analytes. Experimentally, affinity chromatography involves the attachment of affinity ligands to the stationary support. By selecting appropriate ligands having high affinity and specificity towards the target, selective captures of analytes of interest are made possible, allowing their isolation from complex sample matrices. Subsequently, bound analyte species are released from the ligands by employing suitable elution solutions. In addition to the specificity, monolithic stationary phases offer a number of other benefits over conventional particulate supports, i.e., improved mass transfer characteristics, allowing convective rather than diffusional transport of analytes; and high permeability, permitting operations at high flow rates without suffering from backpressure. These benefits result in substantially reduced time requirements for isolation and separation while maintaining satisfactory separation efficiency. Different types of monolithic materials, including organic polymer-based monoliths (e.g., cryogels), inorganic monoliths (e.g., silica monoliths), and hybrid monoliths have been prepared and employed in AMC. A large range of affinity ligands, e.g., proteins, antibodies, immobilized metal ions, dye ligands, have been used with monolithic supports in different formats, and in different applications. The mentioned material-related topics, as well as recent applications of AMC, are discussed in detail in this review. The experimental part of this thesis deals with the isolation of lipoproteins, and low-density lipoprotein (LDL) in particular, from human blood plasma using a newly developed AMC technique. LDL, a globular and major lipid carrier in blood, is diagnostically a highly relevant subclass of lipoproteins due to its involvement in the genesis of atherosclerosis. The currently most frequently employed method for lipoprotein isolation from blood plasma is ultracentrifugation. However, this method suffers from drawbacks, such as being time-consuming, requiring expensive equipment, and the possible exchange of lipids and lipoprotein subclasses during sample processing. Therefore, the first goal was to develop a faster LDL isolation protocol, capable of yielding LDL with good functionality and purity. Thus, the first section reports on the isolation of low-density lipoprotein (LDL) from human blood plasma by employing affinity monolith chromatography method using Convective Interaction Media (CIM) monolithic disk columns as stationary supports. Specifically, anti-apoB100-monoclonal antibody (mAb) was immobilized onto a CIM monolithic disk, providing a suitable capture medium for LDL through its major apolipoprotein, apolipoprotein B100 (apoB100). Other lipoprotein classes, namely very low-density lipoprotein (VLDL) and intermediate-density lipoprotein (IDL), also carry apoB100 and thus may be captured. To discriminate against these lipoproteins, and to obtain LDL with satisfactory purity, an additional CIM monolithic column was immobilized with a glycosaminoglycan, namely chondroitin-6-sulfate (C6S), which also binds lipoproteins, albeit with different specificity and interactions. Both of these affinity media were evaluated for LDL binding either individually or in combination. The quality of the isolated LDL was confirmed with different characterization techniques, such as size exclusion chromatography, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), enzymatic cholesterol and triglyceride assays, and enzymatic-linked immunoassays (ELISAs) specific to apolipoprotein B100 and apolipoprotein E. The results from these multi-method characterizations confirmed the successful LDL isolation with good activity. The second section of the thesis was devoted to quartz crystal microbalance (QCM) biosensor studies of LDL samples isolated from different individuals by different methods (affinity chromatography and conventional ultracentrifugation). A QCM sensor chip immobilized with anti-apoB100 mAb was used and challenged series of different LDL concentrations. The resulting sensorgrams were analyzed with a new numerical algorithm, namely Adaptive Interaction Distribution Algorithm (AIDA), permitting the determination of the number of analyte-receptor binding sites and the underlying kinetics. It was found that the obtained rate constant distributions, and clustering of antibody-LDL complexes were almost identical for all LDL samples, irrespective of sources or isolation techniques. For all samples, a total of five major complex clusters were identified. The major contributions of the two dominating clusters may arise from specific, yet heterogeneous LDL interactions at the antibody binding sites, while the other three clusters observed reflect most likely nonspecific low-affinity interactions from various sources, such as mass transfer effects, and the use of a non-orienting ligand immobilization chemistry

Modern isolation and separation techniques for extracellular vesicles

Extracellular vesicles (EVs) are heterogenous membrane-bound vesicles released from various origins. EVs play a crucial role in cellular communication and mediate several physiological and pathological processes, highlighting their potential therapeutic and diagnostic applications. Due to the rapid increase in interests and needs to elucidate EV properties and functions, numerous isolation and separation approaches for EVs have been developed to overcome limitations of conventional techniques, such as ultracentrifugation. This review focuses on recently emerging and modern EV isolation and separation techniques, including size-, charge-, and affinity-based techniques while excluding ultracentrifugation and precipitation-based techniques due to their multiple limitations. The advantages and drawbacks of each technique are discussed together with insights into their applications. Emerging approaches all share similar features in terms of being time-effective, easy-to-operate, and capable of providing EVs with suitable and desirable purity and integrity for applications of interest. Combination and hyphenation of techniques have been used for EV isolation and separation to yield EVs with the best quality. The most recent development using an automated on-line system including selective affinity-based trapping unit and asymmetrical flow field-flow fractionation allows reliable isolation and fractionation of EV subpopulations from human plasma. (C) 2020 The Author(s). Published by Elsevier B.V.Peer reviewe

Automated on-line isolation and fractionation system for nanosized biomacromolecules from human plasma

An automated on-line isolation and fractionation system including controlling software was developed for selected nanosized biomacromolecules from human plasma by on-line coupled immunoaffinity chromatography-asymmetric flow field-flow fractionation (IAC-AsFlFFF). The on-line system was versatile, only different monoclonal antibodies, anti-apolipoprotein B-100, anti-CD9, or anti-CD61, were immobilized on monolithic disk columns for isolation of lipoproteins and extracellular vesicles (EVs). The platelet-derived CD61-positive EVs and CD9-positive EVs, isolated by IAC, were further fractionated by AsFlFFF to their size-based subpopulations (e.g., exomeres and exosomes) for further analysis. Field-emission scanning electron microscopy elucidated the morphology of the subpopulations, and 20 free amino acids and glucose in EV subpopulations were identified and quantified in the ng/mL range using hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS). The study revealed that there were significant differences between EV origin and size-based subpopulations. The on-line coupled IAC-AsFlFFF system was successfully programmed for reliable execution of 10 sequential isolation and fractionation cycles (37–80 min per cycle) with minimal operator involvement, minimal sample losses, and contamination. The relative standard deviations (RSD) between the cycles for human plasma samples were 0.84–6.6%.Peer reviewe

Automated On-Line Isolation and Fractionation Method for Subpopulations of Extracellular Vesicles

Immunoaffinity chromatography (IAC) with selective antibodies immobilized on polymeric monolithic disk columns enables selective isolation of biomacromolecules from human plasma, while asymmetrical flow field-flow fractionation (AsFlFFF or AF4) can be used for further fractionation of relevant subpopulations of biomacromolecules (e.g., small dense low-density lipoproteins, exomeres, and exosomes) from the isolates. Here we describe how the isolation and fractionation of subpopulations of extracellular vesicles can be achieved without the presence of lipoproteins using on-line coupled IAC-AsFlFFF. With the developed methodology, it is possible to have fast, reliable, and reproducible automated isolation and fractionation of challenging biomacromolecules from human plasma with a high purity and high yields of subpopulations.Peer reviewe

Rapid affinity chromatographic isolation method for LDL in human plasma by immobilized chondroitin-6-sulfate and anti-apoB-100 antibody monolithic disks in tandem

Low-density lipoprotein (LDL) is considered the major risk factor for the development of atherosclerotic cardiovascular diseases (ASCVDs). A novel and rapid method for the isolation of LDL from human plasma was developed utilising affinity chromatography with monolithic stationary supports. The isolation method consisted of two polymeric monolithic disk columns, one immobilized with chondroitin-6-sulfate (C6S) and the other with apolipoprotein B-100 monoclonal antibody (anti-apoB-100 mAb). The first disk with C6S was targeted to remove chylomicrons, very-low-density lipoprotein (VLDL) particles, and their remnants including intermediate-density lipoprotein (IDL) particles, thus allowing the remaining major lipoprotein species, i.e. LDL, lipoprotein(a) (Lp(a)), and high-density lipoprotein (HDL) to flow to the anti-apoB-100 disk. The second disk captured LDL particles via the anti-apoB-100 mAb attached on the disk surface in a highly specific manner, permitting the selective LDL isolation. The success of LDL isolation was confirmed by different techniques including quartz crystal microbalance. In addition, the method developed gave comparable results with ultracentrifugation, conventionally used as a standard method. The reliable results achieved together with a short isolation time (less than 30 min) suggest the method to be suitable for clinically relevant LDL functional assays.Peer reviewe