Biology subjects

Matthews, J. M.

Publications and source records attributed to Matthews, J. M..

3 recordsLinked to original sources

bioRxiv2022

OrganoID: a versatile deep learning platform for organoid image analysis

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications.

bioengineering↗

bioRxiv2021

Elongated sample plot shapes produce higher measurement precision in clustering populations

Monitoring the density of natural populations is crucial for ecosystem management decision making and natural resource management. The most widely used method to measure the population density of animal and plant species in natural habitats is to count organisms in sample plots. Yet evaluation of survey performance by different sample plot shapes, e.g. quadrats compared with transects, has been largely neglected since the 1990s and has not been undertaken using simulation. Simulating populations and surveys, we evaluated population density measurement precision for 900 cases, testing 30 sample plot survey designs in each of 30 spatially clustered populations. We varied three design options: elongation of plot shape while keeping sample area constant, systematic or random plot allocation, and sample size. Survey design performance varied markedly: elongating the plot shape always improved survey precision; allocating plots systematically sometimes did. (i) Averaged across all tested populations, elongated (1:100) transect plot shapes were 2-to-3 times more precise than square (10:10) quadrats. (ii) The precision of systematic surveys accelerated with sample plot number, increasing faster than the (known) linear increase under simple random sampling. This non-linear, concave upward, dependence of systematic precision on sample size has not previously been reported. (iii) The most precise design we evaluated used long narrow transects allocated systematically. Averaging among all 30 tested populations, a researcher would need 600 random square (10:10) quadrats to equal the precision achieved by 100 systematic (1:100) transects. Finding this average efficiency difference of 600% for a survey sample size of 100 plots, these simulation results imply that field trips requiring five sampling days using random quadrats could achieve equal precision in one or two days using systematic elongated transects. For all clustered populations we tested, long narrow transects resulted in a more efficient design for sample plot survey.

ecology↗

bioRxiv2019

Cyclic peptides can engage a single binding pocket through multiple, entirely divergent modes

Cyclic peptide display screening techniques can identify drug leads and biological probes with exceptional affinity and specificity. To date, however, the structural and functional diversity encoded in such peptide libraries remains unexplored. We have used the Random nonstandard Peptide Integrated Discovery (RaPID) system to develop cyclic peptide inhibitors of several acetyllysine-binding bromodomains from the Bromodomain and Extra-Terminal domain (BET) family of epigenetic regulators. These peptides have very high affinities for their targets and exhibit extraordinary selectivity (up to 106-fold), making them the highest-affinity and most specific BET-binding molecules discovered to date. Crystal structures of 13 distinct peptide-bromodomain complexes, which all target the acetyllysine-binding pocket, reveal remarkable diversity in both peptide structure and binding mode, and include both -helical and {beta}-sheet type structures. The peptides can exhibit a high degree of structural pre-organization and bivalent binding of two BDs by one peptide was common, flagging the potential for a new direction in inhibitor design that could bring stronger discrimination between BET-family paralogues. Our data demonstrate for the first time the enormous potential held in these libraries to provide a wide array of modes against a single target, maximizing the opportunity to attain high potency and specificity ligands to a wide variety of proteins.

biochemistry↗