Microfluidic diffusional sizing (MDS) in the literature

Published on December 1st, 2021

Here you can find a summary of all the papers showing the research behind Fluidic Analytics and microfluidic diffusional sizing (MDS). As well as seeing where others have used our products to make amazing discoveries. Below you can find summaries of these papers as well as links to the papers themselves. Don’t forget to sign up to our mailing list so you can stay up to date on new papers and application notes.

Featured Scientific Publications

Our most significant scientific publications include:

Kinetic fingerprints differentiate the mechanisms of action of anti-Aβ antibodies

Fluidic technology reveals the differences in the antibody affinity and stoichiometry for four clinical stage anti-Abeta drug candidates to treat Alzheimer’s Disease

Linse et al., Nat. Struct. Mol. Biol., 2020, 27, 1125-1133. DOI: 10.1038/s41594-020-0505-6

The amyloid cascade hypothesis, according to which the self-assembly of amyloid-β peptide (Aβ) is a causative process in Alzheimer’s disease, has driven many therapeutic efforts for the past 20 years. Failures of clinical trials investigating Aβ-targeted therapies have been interpreted as evidence against this hypothesis, irrespective of the characteristics and mechanisms of action of the therapeutic agents, which are highly challenging to assess.

Here, they combine kinetic analyses with quantitative binding measurements to address the mechanism of action of four clinical stage anti-Aβ antibodies, aducanumab, gantenerumab, bapineuzumab and solanezumab. We quantify the influence of these antibodies on the aggregation kinetics and on the production of oligomeric aggregates and link these effects to the affinity and stoichiometry of each antibody for monomeric and fibrillar forms of Aβ. Our results reveal that, uniquely among these four antibodies, aducanumab dramatically reduces the flux of Aβ oligomers.

Rational design of a conformation-specific antibody for the quantification of Aβ oligomers

Microfluidic diffusional sizing helps elucidate the specificity and selectivity of designed antibodies against A-beta oligomers

Aprile et al., PNAS, 2020, 117 (24), 13509 – 13518. DOI: 10.1073/pnas.1919464117

Protein misfolding and aggregation is the hallmark of numerous human disorders, including Alzheimer’s disease. This process involves the formation of transient and heterogeneous soluble oligomers, some of which are highly cytotoxic. A major challenge for the development of effective diagnostic and therapeutic tools is thus the detection and quantification of these elusive oligomers.

Here, to address this problem, they develop a two-step rational design method for the discovery of oligomer-specific antibodies. The first step consists of an “antigen scanning” phase in which an initial panel of antibodies is designed to bind different epitopes covering the entire sequence of a target protein. This procedure enables the determination through in vitro assays of the regions exposed in the oligomers but not in the fibrillar deposits. The second step involves an “epitope mining” phase, in which a second panel of antibodies is designed to specifically target the regions identified during the scanning step.

They illustrate this method in the case of the amyloid β (Aβ) peptide, whose oligomers are associated with Alzheimer’s disease. Their results show that this approach enables the accurate detection and quantification of Aβ oligomers in vitro, and in Caenorhabditis elegans and mouse hippocampal tissues.

Microfluidic Affinity Profiling reveals a Broad Range of Target Affinities for Anti-SARS-CoV-2 Antibodies in Plasma of Covid Survivors

Clinical researchers discover the spectrum of antibody affinity from plasma of Covid-patients using Fluidic technology

Schneider et al., medRxiv, 2020, 20196907. DOI: 10.1101/2020.09.20.20196907

The clinical outcome of SARS-CoV-2 infections can range from asymptomatic to lethal, and is thought to be crucially shaped by the quality of the immune response which includes antibody titres and affinity for their targets. Using Microfluidic Antibody Affinity Profiling (MAAP), they determined the aggregate affinities and concentrations of anti-SARS-CoV-2 antibodies in plasma samples of 42 seropositive individuals, 23 of whom were confirmed to be SARS-CoV-2-positive by PCR testing.

They found that dissociation constants (KD) of anti-RBD antibodies spanned more than two orders of magnitude from 80 pM to 25 nM, despite having similar antibody concentrations. Individual patients showed progressively higher antibody concentrations but constant KD values, suggesting that affinities did not mature over time. 33 sera showed affinities higher than that of the CoV2 spike for its ACE2 receptor. Accordingly, addition of seropositive plasma to pre-formed spike-ACE2 receptor complexes led to their dissociation.

Finally, they observed that the RBD of HKU1, OC43, and SARS-CoV coronaviruses, but not unrelated control proteins, were able to compete substantially with the RBD of SARS-CoV-2 in solution. Therefore, the affinity of total plasma immunoglobulins to SARS-CoV-2 is an indicator of the quality of the immune response to SARS-CoV-2, and may help select the most efficacious samples for therapeutic plasmapheresis.

Microfluidic diffusional sizing (MDS) in the literature

  1. Schneider et al., Microfluidic characterisation reveals broad range of SARS-CoV-2 antibody affinity in human plasma,
  2. Bocharov et al., All-d-Enantiomeric Peptide D3 Designed for Alzheimer’s Disease Treatment Dynamically Interacts with Membrane-Bound Amyloid-β Precursors, J. Med. Chem. 2021, 64, 22, 16464–16479. DOI:
  3. Lattanzi et al., Solubility of Aβ40 peptide, JCIS Open2021, 100024. DOI: 10.1016/j.jciso.2021.100024
  4. Fiedler et al., Mutations in two SARS-CoV-2 variants of concern reflect two distinct strategies of antibody escape, bioRxiv 2021.07.23.453327. DOI: 10.1101/2021.07.23.453327
  5. Denninger et al., Understanding the role of memory re-activation and cross-reactivity in the defense against SARS-CoV-2. bioRxiv 2021.07.23.453352. DOI: 10.1101/2021.07.23.453352
  6. Laserna et al., Protein Conjugation by Electrophilic Alkynylation Using 5-(Alkynyl)dibenzothiophenium Triflates. Bioconjugate Chem2021,  32(8), 1570–1575. DOI: 10.1021/acs.bioconjchem.1c00317
  7. Samarina et al., Recruitment of phospholipase Cγ1 to the non-structural membrane protein pK15 of Kaposi Sarcoma-associated herpesvirus promotes its Src-dependent phosphorylation. PLoS Pathog202117 (6), e1009635. DOI: 10.1371/journal.ppat.1009635
  8. Fiedler et al., Antibody Affinity Governs the Inhibition of SARS-CoV-2 Spike/ACE2 Binding in Patient Serum. ACS Infect. Dis., 2021, 7(8), 2362–2369. DOI: 10.1021/acsinfecdis.1c00047
  9. Emmenegger et al., LAG3 is not expressed in human and murine neurons and does not modulate α-synucleinopathies. DOI: 10.1101/2021.04.25.441302
  10. Pansieri et al., Templating S100A9 amyloids on Aβ fibrillar surfaces revealed by charge detection mass spectrometry, microscopy, kinetic and microfluidic analyses. Chem. Sci. 202011, 7031-7039. DOI: 10.1039/C9SC05905A
  11. Aprile et al., Rational design of a conformation-specific antibody for the quantification of Aβ oligomers. PNAS, 2020117 (24), 13509-13518. DOI: 10.1073/pnas.1919464117
  12. Schneider et al., Microfluidic Antibody Affinity Profiling for In-Solution Characterisation of Alloantibody – HLA Interactions in Human Serum. bioRxiv, 2020, 296442. DOI: 10.1101/2020.09.14.296442
  13. Schneider et al., Microfluidic Affinity Profiling reveals a Broad Range of Target Affinities for Anti-SARS-CoV-2 Antibodies in Plasma of Covid Survivors. medRxiv, 2020, 20196907. DOI: 10.1101/2020.09.20.20196907
  14. Linse et al., Kinetic fingerprints differentiate the mechanisms of action of anti-Aβ antibodies. Nat. Struct. Mol. Biol., 202027, 1125-1133. DOI: 10.1038/s41594-020-0505-6
  15. Hoppen and Growth., Novel insights into the transfer routes of the essential copper cofactor to the ethylene plant hormone receptor family. Taylor & Francis, 2020, 1716512. DOI: 10.1080/15592324.2020.1716512
  16. Wright et al., Analysis of αB-crystallin polydispersity in solution through native microfluidic electrophoresis. Analyst, 2019144, 4413-4424. DOI: 10.1039/C9AN00382G
  17. Azouz et al., Microfluidic diffusional sizing probes lipid nanodiscs formation. BBA – Biomembranes, 20201862, 183215. DOI: 10.1016/j.bbamem.2020.183215
  18. Macikova et al., Putative interaction site for membrane phospholipids controls activation of TRPA1 channel at physiological membrane potentials. The FEBS Journal, 2019, 14931. DOI: 10.1111/febs.14931
  19. Gang et al., A microfluidic diffusion platform for characterizing the size of lipid vesicles and the thermodynamics of protein-lipid interactions. Anal. Chem., 201890, 3284-3290. DOI: 10.1021/acs.analchem.7b04820
  20. Scheidt et al., Secondary nucleation and elongation occur at different sites on Alzheimer’s amyloid-β aggregates. Science Advances, 20195, eaau3112. DOI: 10.1126/sciadv.aau3112
  21. Falke et al., α-Synuclein-derived lipoparticles in the study of α-Synuclein amyloid fibril formation. Chemistry and Physics of Lipids, 2019220, 57-65.  DOI: 10.1016/j.chemphyslip.2019.02.009
  22. Wright et al., Cooperative Assembly of Hsp70 Subdomain Clusters. Biochemistry, 201857, 3641-3649. DOI: 10.1021/acs.biochem.8b00151
  23. Saar et al., On-chip label-free protein analysis with downstream electrodes for direct removal of electrolysis products. Lab Chip, 201818, 162-170. DOI: 10.1039/C7LC00797C
  24. Lapinska et al., Gradient-free determination of isoelectric points of proteins on chip. Phys. Chem. Chem. Phys., 201719, 23060-23067. DOI: 10.1039/C7CP01503H
  25. Zhang et al., Protein Aggregate-Ligand Binding Assays Based on Microfluidic Diffusional Separation. ChemBioChem., 201617, 1920-1924.  DOI: 10.1002/cbic.201600384
  26. Herling et al., A Microfluidic Platform for Real-Time Detection and Quantification of Protein-Ligand Interactions. Biophysical Journal. 2016110, 1957‑1966. DOI: 10.1016%2Fj.bpj.2016.03.038
  27. Arosio et al., Microfluidic diffusion viscometer for rapid analysis of complex solutions. Anal. Chem., 201688, 488‑3493. DOI: 10.1021/acs.analchem.5b02930
  28. Arosio et al., Microfluidic diffusion analysis of the sizes and interactions of proteins under native solution conditions. ACS Nano., 201610, 333-341. DOI: 10.1021/acsnano.5b04713
  29. Yates et al., Latent analysis of unmodified biomolecules and their complexes in solution with attomole detection sensitivity. Nature Chemistry, 2015, 7, 802-809. DOI: 10.1038/nchem.2344