We study long range density fluctuations (hyperuniformity) in two-dimensional jammed packings of bidisperse droplets. Taking advantage of microfluidics, we systematically span a large range of size and concentration ratios of the two droplet populations. We identify various defects increasing long range density fluctuations mainly due to organization of local particle environment. By choosing an appropriate bidispersity, we fabricate materials with a high level of hyperuniformity. Interesting transparency properties of these optimized materials are established based on numerical simulations.

Human pluripotent stem cells (hPSCs) hold great potential for industrial and clinical applications. Clinical-grade scaffolds and high-quality hPSCs are required for cell expansion as well as easy handling and manipulation of the products. Current hPSC culture methods do not fulfill these requirements because of a lack of proper extracellular matrices (ECMs) and cell culture wares. We developed a layered nano-on-micro fibrous cellular matrix mimicking ECM, named "fiber-on-fiber (FF)" matrix, which enables easy handling and manipulation of cultured cells. While non-woven sheets of cellulose and polyglycolic acid were used as a microfiber layer facilitating mechanical stability, electrospun gelatin nanofibers were crosslinked on the microfiber layer, generating a mesh structure with connected nanofibers facilitating cell adhesion and growth. Our results showed that the FF matrix supports effective hPSC culture with maintenance of their pluripotency and normal chromosomes over two months, as well as effective scaled-up expansion, with fold increases of 54.1 ± 15.6 and 40.4 ± 8.4 in cell number per week for H1 human embryonic stem cells and 253G1 human induced pluripotent stem cells, respectively. This simple approach to mimick the ECM may have important implications after further optimization to generate lineage-specific products.

Most spindle-shaped cells (including smooth muscles and sarcomas) organize in vivo into well-aligned ‘nematic’ domains1, 2, 3, creating intrinsic topological defects that may be used to probe the behaviour of these active nematic systems. Active non-cellular nematics have been shown to be dominated by activity, yielding complex chaotic flows4, 5. However, the regime in which live spindle-shaped cells operate, and the importance of cell–substrate friction in particular, remains largely unexplored. Using in vitro experiments, we show that these active cellular nematics operate in a regime in which activity is effectively damped by friction, and that the interaction between defects is controlled by the system’s elastic nematic energy. Due to the activity of the cells, these defects behave as self-propelled particles and pairwise annihilate until all displacements freeze as cell crowding increases6, 7. When confined in mesoscopic circular domains, the system evolves towards two identical +1/2 disclinations facing each other. The most likely reduced positions of these defects are independent of the size of the disk, the cells’ activity or even the cell type, but are well described by equilibrium liquid crystal theory. These cell-based systems thus operate in a regime more stable than other active nematics, which may be necessary for their biological function.

Inside individual cells, expression of genes is inherently stochastic and manifests as cell-to-cell variability or noise in protein copy numbers. Since proteins half-lives can be comparable to the cell-cycle length, randomness in cell-division times generates additional intercellular variability in protein levels. Moreover, as many mRNA/protein species are expressed at low-copy numbers, errors incurred in partitioning of molecules between two daughter cells are significant. We derive analytical formulas for the total noise in protein levels when the cell-cycle duration follows a general class of probability distributions. Using a novel hybrid approach the total noise is decomposed into components arising from i) stochastic expression; ii) partitioning errors at the time of cell division and iii) random cell-division events. These formulas reveal that random cell-division times not only generate additional extrinsic noise, but also critically affect the mean protein copy numbers and intrinsic noise components. Counter intuitively, in some parameter regimes, noise in protein levels can decrease as cell-division times become more stochastic. Computations are extended to consider genome duplication, where transcription rate is increased at a random point in the cell cycle. We systematically investigate how the timing of genome duplication influences different protein noise components. Intriguingly, results show that noise contribution from stochastic expression is minimized at an optimal genome-duplication time. Our theoretical results motivate new experimental methods for decomposing protein noise levels from synchronized and asynchronized single-cell expression data. Characterizing the contributions of individual noise mechanisms will lead to precise estimates of gene expression parameters and techniques for altering stochasticity to change phenotype of individual cells.

The appearance of molecular replicators (molecules that can be copied) was probably a critical step in the origin of life. However, parasitic replicators would take over and would have prevented life from taking off unless the replicators were compartmentalized in reproducing protocells. Paradoxically, control of protocell reproduction would seem to require evolved replicators. We show here that a simpler population structure, based on cycles of transient compartmentalization (TC) and mixing of RNA replicators, is sufficient to prevent takeover by parasitic mutants. TC tends to select for ensembles of replicators that replicate at a similar rate, including a diversity of parasites that could serve as a source of opportunistic functionality. Thus, TC in natural, abiological compartments could have allowed life to take hold.

De novo biocatalysts with non-natural functionality are accessible by computational enzyme design. The catalytic activities obtained for the initial designs are usually low, but can be optimized significantly by directed evolution. Nevertheless, rate accelerations approaching the level of natural enzymes can only be achieved over many rounds of tedious and time-consuming laboratory evolution. In this work, we show that microfluidic-based screening using fluorescence-activated droplet sorting (FADS) is ideally suited for efficient optimization of designed enzymes with low starting activity, essentially straight out of the computer. We chose the designed retro-aldolase RA95.0, which had been previously evolved by conventional microtiter plate screening, as an example and reoptimized it using the microfluidic-based assay. Our results show that FADS is sufficiently sensitive to detect enzyme activities as low as kcat/Km = 0.5 M(-1)s(-1) The ultra-high throughput of this system makes screening of large mutant libraries possible in which clusters of up to five residues are randomized simultaneously. Thus, combinations of beneficial mutations can be identified directly, leading to large jumps in catalytic activity of up to 80-fold within a single round of evolution. By exploring several evolutionary trajectories in parallel, we identify alternative active site arrangements that exhibit comparably enhanced efficiency but opposite enantioselectivity

Variation and selection are the core principles of Darwinian evolution, but quantitatively relating the diversity of a population to its capacity to respond to selection is challenging. Here, we examine this problem at a molecular level in the context of populations of partially randomized proteins selected for binding to well-defined targets. We built several minimal protein libraries, screened them in vitro by phage display, and analyzed their response to selection by high-throughput sequencing. A statistical analysis of the results reveals two main findings. First, libraries with the same sequence diversity but built around different "frameworks" typically have vastly different responses; second, the distribution of responses of the best binders in a library follows a simple scaling law. We show how an elementary probabilistic model based on extreme value theory rationalizes the latter finding. Our results have implications for designing synthetic protein libraries, estimating the density of functional biomolecules in sequence space, characterizing diversity in natural populations, and experimentally investigating evolvability (i.e., the potential for future evolution).

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes–via growth–over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.

Measurements and simulations have found that water moves through carbon nanotubes at exceptionally high rates owing to nearly frictionless interfaces1, 2, 3, 4. These observations have stimulated interest in nanotube-based membranes for applications including desalination, nano-filtration and energy harvesting5, 6, 7, 8, 9, 10, yet the exact mechanisms of water transport inside the nanotubes and at the water–carbon interface continue to be debated11, 12 because existing theories do not provide a satisfactory explanation for the limited number of experimental results available so far13. This lack of experimental results arises because, even though controlled and systematic studies have explored transport through individual nanotubes7, 8, 9, 14, 15, 16, 17, none has met the considerable technical challenge of unambiguously measuring the permeability of a single nanotube11. Here we show that the pressure-driven flow rate through individual nanotubes can be determined with unprecedented sensitivity and without dyes from the hydrodynamics of water jets as they emerge from single nanotubes into a surrounding fluid. Our measurements reveal unexpectedly large and radius-dependent surface slippage in carbon nanotubes, and no slippage in boron nitride nanotubes that are crystallographically similar to carbon nanotubes, but electronically different. This pronounced contrast between the two systems must originate from subtle differences in the atomic-scale details of their solid–liquid interfaces, illustrating that nanofluidics is the frontier at which the continuum picture of fluid mechanics meets the atomic nature of matter.

A microfluidic method to specifically capture and detect infectious bacteria based on immunorecognition and proliferative power is presented. It involves a microscale fluidized bed in which magnetic and drag forces are balanced to retain antibody-functionalized superparamagnetic beads in a chamber during sample perfusion. Captured cells are then cultivated in situ by infusing nutritionally-rich medium. The system was validated by the direct one-step detection of Salmonella Typhimurium in undiluted unskimmed milk, without pre-treatment. The growth of bacteria induces an expansion of the fluidized bed, mainly due to the volume occupied by the newly formed bacteria. This expansion can be observed with the naked eye, providing simple low-cost detection of only a few bacteria and in a few hours. The time to expansion can also be measured with a low-cost camera, allowing quantitative detection down to 4 cfu (colony forming unit), with a dynamic range of 100 to 107 cfu ml−1 in 2 to 8 hours, depending on the initial concentration. This mode of operation is an equivalent of quantitative PCR, with which it shares a high dynamic range and outstanding sensitivity and specificity, operating at the live cell rather than DNA level. Specificity was demonstrated by controls performed in the presence of a 500× excess of non-pathogenic Lactococcus lactis. The system's versatility was demonstrated by its successful application to the detection and quantitation of Escherichia coli O157:H15 and Enterobacter cloacae. This new technology allows fast, low-cost, portable and automated bacteria detection for various applications in food, environment, security and clinics.