Biology subjects

Holland, J.

Publications and source records attributed to Holland, J..

4 recordsLinked to original sources

bioRxiv2026

Millisecond nonlinear state changes during droplet coalescence identify therapeutic-antibody developability liabilities

Apoha's Liquid State Machine records ellipsometric waveforms from injections depositing sub-microgram quantities of antibody drop-by-drop onto a liquid reservoir. We previously showed that a behavioural feature extracted from the waveforms, VIBE1, identified antibodies carrying multiple biophysical liabilities in an industrial dataset of 71 monoclonal antibodies, and enriched for clinical failure across a larger dataset of 235 therapeutic antibodies. Here, we use an auxiliary coalescence-sensor channel to decode VIBE1 by separating the coalescence event from its propagation through the substrate. The per-titration drop-to-drop standard deviation of pinch-off time, {sigma}{tau}, explains most of VIBE1's variance across the dataset (R2 = 0.92, n = 1182). High-speed imaging at 10,000 frames per second reveals that all imaged drops initially thin at the same Newtonian capillary-inertial rate while the neck remains wide. In drops from certain antibodies, the thinning bridge then decelerates as internal strain builds in the narrowing neck. This elastocapillary stiffening response has a timescale {lambda} that decreases as pinch-off time {tau}i increases across the imaged set. {sigma}{tau} is therefore a readout of the antibody's propensity to undergo a transient gel-like stiffening response during coalescence, and that variability is what VIBE1 captures. The signal is concentration dependent, and absent in bovine serum albumin (BSA) tested at up to an order of magnitude higher concentration than the antibodies, despite BSA being a strongly surface-active globular protein. The instrument is configured so that complex behaviours of this kind appear in its recorded waveforms; the gel-like coalescence response we identify here is one such phenomenon.

biophysics↗

bioRxiv2020

Repulsive electrostatic interactions modulate dense and dilute phase properties of biomolecular condensates

Liquid-like membraneless organelles form via multiple, weak interactions between biomolecules. The resulting condensed states constitute novel solvent environments inside eukaryotic cells that partition biomolecules and may favour particular biochemical reactions. Here we demonstrate that, in addition to attractive interactions, repulsive electrostatic interactions modulate condensate properties. We find that net charge modulates the formation, morphology and solvent properties of model Ddx4 condensates in cells and in vitro and that a net negative charge is conserved across germ cell-specific Ddx4 orthologues. This conserved net charge provides a sensitivity to multivalent cations that is not observed in somatic paralogues. The disfavouring effect of a net negative charge in Ddx4 orthologues appears to be offset by increased charge patterning, indicating that fine tuning of both attractive and repulsive interactions can create responsive solvent environments inside biomolecular condensates.

cell biology↗

bioRxiv2020

An essential amino acid synchronises malaria parasite development with daily host rhythms

Rapid asexual replication of blood stage malaria parasites is responsible for the severity of disease symptoms and fuels the production of transmission forms. That malaria parasite species coordinate their cycles of asexual replication with daily rhythms of their host was discovered in the Hippocratic era, but how and why this occurs is enigmatic. Here, we demonstrate that the Plasmodium chabaudis schedule for asexual replication can be orchestrated by a isoleucine, metabolite provided to the parasite in periodic manner due to the hosts rhythmic intake of food. First, we identify nutrients with daily rhythms in the blood that match the timing of rhythms in both host feeding and the developmental schedule of asexually replicating parasites. We hypothesise that if parasites set their own developmental schedule, they should use a time-of-day cue that is a factor they cannot generate endogenously at any time-of-day, or scavenge in a round-the-clock manner. Our large-scale metabolomics experiment reveals that only one metabolite - the amino acid isoleucine - fits these criteria. Second, further experiments reveal that parasites alter the developmental schedule of asexual stages in response to isoleucine provision and withdrawal in the manner consistent with it acting as a time-cue. Specifically, parasites respond to isoleucine loss by slowing development. This is a parasite strategy rather than the consequences of an imposed constraint, because unlike when parasites are deprived of other essential nutrients, they suffer no apparent costs in the absence of isoleucine. Overall, our data suggest parasites can use the daily rhythmicity of blood-isoleucine concentration to synchronise asexual development with the availability of isoleucine, and potentially other resources, that arrive in the blood in a periodic manner due to the hosts daily feeding-fasting cycle. Identifying both how and why parasites keep time opens avenues for interventions; interfering with the parasites time-keeping mechanism may stall replication, increasing the efficacy of drugs and immune responses, and could also prevent parasites from entering dormancy to tolerate drugs.

microbiology↗

bioRxiv2017

Comparison of one-stage and two-stage genome-wide association studies

Linear mixed models are widely used in humans, animals, and plants to conduct genome-wide association studies (GWAS). A characteristic of experimental designs for plants is that experimental units are typically multiple-plant plots of families or lines that are replicated across environments. This structure can present computational challenges to conducting a genome scan on raw (plot-level) data. Two-stage methods have been proposed to reduce the complexity and increase the computational speed of whole-genome scans. The first stage of the analysis fits raw data to a model including environment and line effects, but no individual marker effects. The second stage involves the whole genome scan of marker tests using summary values for each line as the dependent variable. Missing data and unbalanced experimental designs can result in biased estimates of marker association effects from two-stage analyses. In this study, we developed a weighted two-stage analysis to reduce bias and improve power of GWAS while maintaining the computational efficiency of two-stage analyses. Simulation based on real marker data of a diverse panel of maize inbred lines was used to compare power and false discovery rate of the new weighted two-stage method to single-stage and other two-stage analyses and to compare different two-stage models. In the case of severely unbalanced data, only the weighted two-stage GWAS has power and false discovery rate similar to the one-stage analysis. The weighted GWAS method has been implemented in the open-source software TASSEL.

genetics↗