This paper reports a method for the production of arrays of nanolitre plugs with distinct chemical compositions. One of the primary constraints on the use of plug-based microfluidics for large scale biological screening is the difficulty of fabricating arrays of chemically distinct plugs on the nanolitre scale. Here, using microfluidic devices with several T-junctions linked in series, a single input array of large (approximately 320 nL) plugs was split to produce 16 output arrays of smaller (approximately 20 nL) plugs; the composition and configuration of these arrays were identical to that of the input. This paper shows how the passive break-up of plugs in T-junction microchannel geometries can be used to produce a set of smaller-volume output arrays useful for chemical screening from a single large-volume array. A simple theoretical description is presented to describe splitting as a function of the Capillary number, the capillary pressure, the total pressure difference across the channel, and the geometric fluidic resistance. By accounting for these considerations, plug coalescence and plug-plug contamination can be eliminated from the splitting process and the symmetry of splitting can be preserved. Furthermore, single-outlet splitting devices were implemented with both valve- and volume-based methods for coordinating the release of output arrays. Arrays of plugs containing commercial sparse matrix screens were obtained from the presented splitting method and these arrays were used in protein crystallization trials. The techniques presented in this paper may facilitate the implementation of high-throughput chemical and biological screening.

This manuscript describes the effect of interfacial tensions on three-phase liquid-liquid-liquid flow in microfluidic channels and the use of this flow to prevent microfluidic plugs from coalescing. One problem in using microfluidic plugs as microreactors is the coalescence of adjacent plugs caused by the relative motion of plugs during flow. Here, coalescence of reagent plugs was eliminated by using plugs of a third immiscible liquid as spacers to separate adjacent reagent plugs. This work tested the requirements of interfacial tensions for plugs of a third liquid to be effective spacers. Two candidates satisfying the requirements were identified, and one of these liquids was used in the crystallization of protein human Tdp1 to demonstrate its compatibility with protein crystallization in plugs. This method for identifying immiscible liquids for use as a spacer will also be useful for applications involving manipulation of large arrays of droplets in microfluidic channels.

Bacterial survival requires the rapid propagation of signals through gene networks during stress, but how this is achieved is not well understood. This study systematically characterizes the signaling dynamics of a cascade of RNA-protein interactions in the CsrA system, which regulates stress responses and biofilm formation in Escherichia coli. Noncoding RNAs are at the center of the CsrA system; target mRNAs are bound by CsrA proteins that inhibit their translation, CsrA proteins are sequestered by CsrB noncoding RNAs, and the degradation of CsrB RNAs is increased by CsrD proteins. Here, we show using in vivo experiments and quantitative modeling that the CsrA system integrates three strategies to achieve rapid and robust signaling. These strategies include: (i) the sequestration of stable proteins by noncoding RNAs, which rapidly inactivates protein activity; (ii) the degradation of stable noncoding RNAs, which enables their rapid removal; and (iii) a negative-feedback loop created by CsrA repression of CsrD production, which reduces the time for the system to achieve steady state. We also demonstrate that sequestration in the CsrA system results in signaling that is robust to growth rates because it does not rely on the slow dilution of molecules via cell division; therefore, signaling can occur even during growth arrest induced by starvation or antibiotic treatment.gene circuit | reverse engineering | synthetic biology | systems biology

Bacteria possess networks of small RNAs (sRNAs) that are important for modulating gene expression. At the center of many of these sRNA networks is the Hfq protein. Hfq's role is to quickly match cognate sRNAs and target mRNAs from among a large number of possible combinations and anneal them to form duplexes. Here we show using a kinetic model that Hfq can efficiently and robustly achieve this difficult task by minimizing the sequestration of sRNAs and target mRNAs in Hfq complexes. This sequestration can be reduced by two non-mutually exclusive kinetic mechanisms. The first mechanism involves heterotropic cooperativity (where sRNA and target mRNA binding to Hfq is influenced by other RNAs bound to Hfq); this cooperativity can selectively decrease singly-bound Hfq complexes and ternary complexes with non-cognate sRNA-target mRNA pairs while increasing cognate ternary complexes. The second mechanism relies on frequent RNA dissociation enabling the rapid cycling of sRNAs and target mRNAs among different Hfq complexes; this increases the probability the cognate ternary complex forms before the sRNAs and target mRNAs degrade. We further demonstrate that the performance of sRNAs in isolation is not predictive of their performance within a network. These findings highlight the importance of experimentally characterizing duplex formation in physiologically relevant contexts with multiple RNAs competing for Hfq. The model will provide a valuable framework for guiding and interpreting these experiments.

Theoretical tools for adequately treating stochastic effects are important for understanding their role in biological processes. Although master equations provide rigorous means for investigating effects associated with fluctuations of discrete molecular copy numbers, they can be very challenging to treat analytically and numerically. Approaches based on the Langevin approximation are often more tractable, but care must be used to ensure that it is justified in each situation. Here, we examine a model of an enzyme cycle for which noise qualitatively alters the behavior of the system: fluctuations in the population of an enzyme can result in amplification and multistability in the distribution of its product. We compare master equation and Langevin treatments of this system and show that results derived previously with a white noise Langevin equation [M. Samoilov et al., Proc. Natl. Acad. Sci. U.S.A. 102, 2310 (2005)] are inconsistent with the master equation. A colored noise Langevin equation captures some, but not all, of the essential physics of the system. The advantages and disadvantages of the Langevin approximation for modeling biological processes are discussed.