Biology subjects

Edwards, M. A.

Publications and source records attributed to Edwards, M. A..

4 recordsLinked to original sources

bioRxiv2023

Nanopore Sensors for Enhanced Detection of Nanoparticles

Nanopore sensing is a technique based on the Coulter principle to analyze and characterize nanoscale materials with single entity resolution. However, its use in nanoparticle characterization has been constrained by the need to tailor the nanopore aperture size to the size of the analyte, precluding the analysis of heterogenous samples. Additionally, nanopore sensors often require the use of high salt concentrations to improve the signal-to-noise ratio, which further limits their ability to study a wide range of nanoparticles that are unstable at high ionic strength. Here, we report the development of nanopore sensors enhanced by a polymer electrolyte system, enabling the analysis of heterogenous nanoparticle mixtures at low ionic strength. We present a finite element model to explain the anomalous conductive/resistive pulse signals observed and compare these results with experiments. Furthermore, we demonstrate the wide applicability of the method by characterizing metallic nanospheres of varied sizes, plasmonic nanostars with various degrees of branching, and protein-based spherical nucleic acids with different oligonucleotide loadings. Our system will complement the toolbox of nanomaterials characterization techniques and will enable real-time optimization workflow for engineering a wide range of nanomaterials.

biophysics↗

bioRxiv2023

A parametric model for estimating the timing and intensity of animal migration

Animals of many different species, trophic levels, and life history strategies migrate, and the improvement of animal tracking technology allows ecologists to collect increasing amounts of detailed data on these movements. Understanding when animals migrate is important for managing their populations, but is still difficult despite modelling advancements. We designed a model that parametrically estimates the timing of migration from animal tracking data. Our model identifies the beginning and end of migratory movements as signaled by changes in step length and turning angle distributions. To this end, we can also use the model to estimate how an animals movement changes when it begins migrating. We tested our model on three datasets: migratory ferruginous hawks (Buteo regalis) in the Great Plains and barren-ground caribou (Rangifer tarandus groenlandicus) in northern Canada, and non-migratory brown bears (Ursus arctos) from the Canadian Arctic. We estimated the beginning and end of migration in caribou and hawks to the nearest day, while confirming a lack of migratory behaviour in the brown bear population. The flexibility of our modelling framework allowed us to assess intricacies associated with each dataset: long-term stopover behaviour in ferruginous hawks and a priori knowledge of caribou calving areas and behaviour. In addition to estimating when caribou and ferruginous hawks migrated, our model also identified differences in how the two populations migrated; ferruginous hawks achieved efficient migrations by increasing their movement rates while caribou migration was achieved through significant increases in directional persistence. Our approach is broadly applicable to many animal movement studies. We anticipate that rigorous assessment of migration metrics will aid understanding of both how and why animals move.

ecology↗

bioRxiv2021

Time-dependent memory and individual variation in Arctic brown bears (Ursus arctos)

1Animal movement modelling provides unique insight about how animals perceive their landscape and how this perception may influence space use. When coupled with data describing an animals environment, ecologists can fit statistical models to location data to describe how spatial memory informs movement. We performed such an analysis on a population of brown bears (Ursus arctos) in the Canadian Arctic using a model incorporating time-dependent spatial memory patterns. Brown bear populations in the Arctic lie on the periphery of the species range, and as a result endure harsh environmental conditions. In this kind of environment, effective use of memory to inform movement strategies could spell the difference between survival and mortality. The model we fit tests four alternate hypotheses (some incorporating memory; some not) against each other, and we found a high degree of individual variation in how brown bears used memory. We found that 52% (11 of 21) of the bears used complex, time-dependent spatial memory to inform their movement decisions. These results, coupled with existing knowledge on individual variation in the population, highlight the diversity of foraging strategies for Arctic brown bears while also displaying the inference that can be drawn from this innovative movement model.

ecology↗

bioRxiv2021

Cooperative electrolyte-PEG interactions drive the signal amplification in a solid-state nanopore

Nanopore systems have emerged as a leading platform for the analysis of biomolecular complexes with single molecule resolution. However, the analysis of several analytes like short nucleic acids or proteins with nanopores represents a sensitivity challenge, because their translocation lead to small signals difficult to distinguish from the noise. Here, we report a simple method to enhance the signal to noise ratio in nanopore experiments by a simple modification of the solution used in nanopore sensing. The addition of poly-ethylene glycol (PEG) and the careful selection of the supporting electrolyte leads to large signal enhancement. We observed that the translocation dynamics are in good agreement with an established method that uses the lattice energy of an electrolyte to approximate the affinity of an ion to PEG. We identified CsBr as the optimal supporting electrolyte to complement PEG to enable the analysis of dsDNA at 500 kHz bandwidth, and the detection of dsDNA as short as 75 bp.

biophysics↗