Optimal Transport Flows for Distributed Production Networks

Network flows often exhibit a hierarchical tree-like structure that can be attributed to the minimisation of dissipation. The common feature of such systems is a single source and multiple sinks (or vice versa). In contrast, here we study networks with only a single source and sink. These systems can arise from secondary purposes of the networks, such as blood sugar regulation through insulin production. Minimisation of dissipation in these systems lead to trivial behaviour. We show instead how optimising the transport time yields network topologies that match those observed in the insulin-producing pancreatic islets. These are patterns of periphery-to-center and center-to-periphery flows. The obtained flow networks are broadly independent of how the flow velocity depends on the flow flux, but continuous and discontinuous phase transitions appear at extreme flux dependencies. Lastly, we show how constraints on flows can lead to buckling of the branches of the network, a feature that is also observed in pancreatic islets

Motility of Colonial Choanoflagellates and the Statistics of Aggregate Random Walkers.

We illuminate the nature of the three-dimensional random walks of microorganisms composed of individual organisms adhered together. Such aggregate random walkers are typified by choanoflagellates, eukaryotes that are the closest living relatives of animals. In the colony-forming species Salpingoeca rosetta we show that the beating of each flagellum is stochastic and uncorrelated with others, and the vectorial sum of the flagellar propulsion manifests as stochastic helical swimming. A quantitative theory for these results is presented and species variability discussed.Work supported by the EPSRC and St. Johns College (JBK), ERC Advanced Investigator Grant 247333 and a Wellcome Trust Senior Investigator Award.This is the final version of the article. It first appeared from American Physical Society via http://dx.doi.org/10.1103/PhysRevLett.116.03810

Filter-feeding, near-field flows, and the morphologies of colonial choanoflagellates

Efficient uptake of prey and nutrients from the environment is an important component in the fitness of all microorganisms, and its dependence on size may reveal clues to the origins of evolutionary transitions to multicellularity. Because potential benefits in uptake rates must be viewed in the context of other costs and benefits of size, such as varying predation rates and the increased metabolic costs associated with larger and more complex body plans, the uptake rate itself is not necessarily that which is optimized by evolution. Uptake rates can be strongly dependent on local organism geometry and its swimming speed, providing selective pressure for particular arrangements. Here we examine these issues for choanoflagellates, filter-feeding microorganisms that are the closest relatives of the animals. We explore the different morphological variations of the choanoflagellate $\textit{Salpingoeca rosetta}$, which can exist as a swimming cell, as a sessile thecate cell, and as colonies of cells in various shapes. In the absence of other requirements and in a homogeneously nutritious environment, we find that the optimal strategy to maximize filter-feeding by the collar of microvilli is to swim fast, which favors swimming unicells. In large external flows, the sessile thecate cell becomes advantageous. Effects of prey diffusion are discussed and also found to be to the advantage of the swimming unicell.This work was supported in part by the Engineering and Physical Sciences Research Council and St. Johns College (J.B.K.) and Wellcome Trust Senior Investigator Award 097855MA (R.E.G.)

Fluctuations in the Kinetics of Linear Protein Self-Assembly.

Biological systems are characterized by compartmentalization from the subcellular to the tissue level, and thus reactions in small volumes are ubiquitous in living systems. Under such conditions, statistical number fluctuations, which are commonly negligible in bulk reactions, can become dominant and lead to stochastic behavior. We present here a stochastic model of protein filament formation in small volumes. We show that two principal regimes emerge for the system behavior, a small fluctuation regime close to bulk behavior and a large fluctuation regime characterized by single rare events. Our analysis shows that in both regimes the reaction lag-time scales inversely with the system volume, unlike in bulk. Finally, we use our stochastic model to connect data from small-volume microdroplet experiments of amyloid formation to bulk aggregation rates, and show that digital analysis of an ensemble of protein aggregation reactions taking place under microconfinement provides an accurate measure of the rate of primary nucleation of protein aggregates, a process that has been challenging to quantify from conventional bulk experiments.We are grateful to St. John’s College, Cambridge (T. C. T. M., J. B. K.), the Schiff Foundation (A. J. D.), the EPSRC (K. L. S.), NSF Grant No. DMR-1310266 (D. A. W.), the Harvard MRSEC Grant No. DMR1420570 (D. A. W.), BBSRC (T. P. J. K.), ERC (T. C. T. M., T. P. J. K.), and Frances and Augustus Newman Foundation (T. P. J. K.) for financial support

Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery.

BACKGROUND: The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation. NEW METHOD: We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously. RESULTS: We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimer's and Parkinson's diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes. COMPARISON WITH EXISTING METHODS: The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals. CONCLUSIONS: The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism