An accurate and reproducible method to measure snake venom anticoagulant activity
Year: 2026
Type: article
Abstract: Anticoagulant activity is an important clinical effect of human envenoming, seen in Australian black snake ( Pseudechis ) and cobra ( Naja ) envenoming. Anticoagulant toxins are not well characterised and anticoagulant assays not standardised. We aimed to develop and validate an accurate and standardised anticoagulant assay for snake venoms. We used a turbidimetric assay previously developed to measure procoagulant activity and modified for anticoagulant activity. Recalcified fresh frozen plasma was mixed with varying concentrations of venom in a buffer for 5 s in a microplate well, and optical density was recorded for 340 nm every 10s in a plate reader. Clotting time was defined as the time until a sharp increase occurred in optical density, which was normalised by dividing the venom clotting time by the plasma control clotting time (CT/CT Pl ). We investigated the effect of changing calcium concentration, the presence of a recombinant tissue factor (Innovin®), venom reconstitution, three different buffers, microplate type, and experimental timing. Optimal conditions were a calcium concentration of 0.4 M, physiological buffer solution (PBS) and a regular microplate. Freshly reconstituted venom and immediately thawed plasma modestly improved the assay. Assay sensitivity improved without a recombinant tissue factor (Innovin®) trigger, particularly for weakly anticoagulant venoms. To reduce assay variability the assays were best done by selecting 4–6 venoms, and doing these on 4–6 days, with each venom at a different time each day; median coefficient of variation for all venoms <10%. The anticoagulant assay had significantly reduced variability and improved sensitivity when conditions were standardised and a triggering agent was not used.
Institution: University of Newcastle Australia
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
OpenAlex ID: W7124259334
