Repeated clinical malaria episodes are associated with modification of the immune system in children.

BACKGROUND: There are over 200 million reported cases of malaria each year, and most children living in endemic areas will experience multiple episodes of clinical disease before puberty. We set out to understand how frequent clinical malaria, which elicits a strong inflammatory response, affects the immune system and whether these modifications are observable in the absence of detectable parasitaemia. METHODS: We used a multi-dimensional approach comprising whole blood transcriptomic, cellular and plasma cytokine analyses on a cohort of children living with endemic malaria, but uninfected at sampling, who had been under active surveillance for malaria for 8 years. Children were categorised into two groups depending on the cumulative number of episodes experienced: high (≥ 8) or low (< 5). RESULTS: We observe that multiple episodes of malaria are associated with modification of the immune system. Children who had experienced a large number of episodes demonstrated upregulation of interferon-inducible genes, a clear increase in circulating levels of the immunoregulatory cytokine IL-10 and enhanced activation of neutrophils, B cells and CD8+ T cells. CONCLUSION: Transcriptomic analysis together with cytokine and immune cell profiling of peripheral blood can robustly detect immune differences between children with different numbers of prior malaria episodes. Multiple episodes of malaria are associated with modification of the immune system in children. Such immune modifications may have implications for the initiation of subsequent immune responses and the induction of vaccine-mediated protection.

Epistasis in a Fitness Landscape Defined by Antibody-Antigen Binding Free Energy.

Epistasis is the phenomenon by which the effect of a mutation depends on its genetic background. While it is usually defined in terms of organismal fitness, for single proteins, it must reflect physical interactions among residues. Here, we systematically extract the specific contribution pairwise epistasis makes to the physical affinity of antibody-antigen binding relevant to affinity maturation, a process of accelerated Darwinian evolution. We find that, among competing definitions of affinity, the binding free energy is the most appropriate to describe epistasis. We show that epistasis is pervasive, accounting for 25%-35% of variability, of which a large fraction is beneficial. This work suggests that epistasis both constrains, through negative epistasis, and enlarges, through positive epistasis, the set of possible evolutionary paths that can produce high-affinity sequences during repeated rounds of mutation and selection.

Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves.

Despite the central role that antibodies play in the adaptive immune system and in biotechnology, much remains unknown about the quantitative relationship between an antibody's amino acid sequence and its antigen binding affinity. Here we describe a new experimental approach, called Tite-Seq, that is capable of measuring binding titration curves and corresponding affinities for thousands of variant antibodies in parallel. The measurement of titration curves eliminates the confounding effects of antibody expression and stability that arise in standard deep mutational scanning assays. We demonstrate Tite-Seq on the CDR1H and CDR3H regions of a well-studied scFv antibody. Our data shed light on the structural basis for antigen binding affinity and suggests a role for secondary CDR loops in establishing antibody stability. Tite-Seq fills a large gap in the ability to measure critical aspects of the adaptive immune system, and can be readily used for studying sequence-affinity landscapes in other protein systems.

Subwavelength grating enabled on-chip ultra-compact optical true time delay line.

An optical true time delay line (OTTDL) is a basic photonic building block that enables many microwave photonic and optical processing operations. The conventional design for an integrated OTTDL that is based on spatial diversity uses a length-variable waveguide array to create the optical time delays, which can introduce complexities in the integrated circuit design. Here we report the first ever demonstration of an integrated index-variable OTTDL that exploits spatial diversity in an equal length waveguide array. The approach uses subwavelength grating waveguides in silicon-on-insulator (SOI), which enables the realization of OTTDLs having a simple geometry and that occupy a compact chip area. Moreover, compared to conventional wavelength-variable delay lines with a few THz operation bandwidth, our index-variable OTTDL has an extremely broad operation bandwidth practically exceeding several tens of THz, which supports operation for various input optical signals with broad ranges of central wavelength and bandwidth.

Stress-response balance drives the evolution of a network module and its host genome.

Stress response genes and their regulators form networks that underlie drug resistance. These networks often have an inherent tradeoff: their expression is costly in the absence of stress, but beneficial in stress. They can quickly emerge in the genomes of infectious microbes and cancer cells, protecting them from treatment. Yet, the evolution of stress resistance networks is not well understood. Here, we use a two-component synthetic gene circuit integrated into the budding yeast genome to model experimentally the adaptation of a stress response module and its host genome in three different scenarios. In agreement with computational predictions, we find that: (i) intra-module mutations target and eliminate the module if it confers only cost without any benefit to the cell; (ii) intra- and extra-module mutations jointly activate the module if it is potentially beneficial and confers no cost; and (iii) a few specific mutations repeatedly fine-tune the module's noisy response if it has excessive costs and/or insufficient benefits. Overall, these findings reveal how the timing and mechanisms of stress response network evolution depend on the environment.

Two-dimensionality of yeast colony expansion accompanied by pattern formation.

Yeasts can form multicellular patterns as they expand on agar plates, a phenotype that requires a functional copy of the FLO11 gene. Although the biochemical and molecular requirements for such patterns have been examined, the mechanisms underlying their formation are not entirely clear. Here we develop quantitative methods to accurately characterize the size, shape, and surface patterns of yeast colonies for various combinations of agar and sugar concentrations. We combine these measurements with mathematical and physical models and find that FLO11 gene constrains cells to grow near the agar surface, causing the formation of larger and more irregular colonies that undergo hierarchical wrinkling. Head-to-head competition assays on agar plates indicate that two-dimensional constraint on the expansion of FLO11 wild type (FLO11) cells confers a fitness advantage over FLO11 knockout (flo11Δ) cells on the agar surface.

Wavelength conversion of 28 GBaud 16-QAM signals based on four-wave mixing in a silicon nanowire.

We demonstrate error-free wavelength conversion of 28 GBaud 16-QAM single polarization (112 Gb/s) signals based on four-wave mixing in a dispersion engineered silicon nanowire (SNW). Wavelength conversion covering the entire C-band is achieved using a single pump. We characterize the performance of the wavelength converter subsystem through the electrical signal to noise ratio penalty as well as the bit error rate of the converted signal as a function of input signal power. Moreover, we evaluate the degradation of the optical signal to noise ratio due to wavelength conversion in the SNW.

Nanowires and sidewall Bragg gratings in silicon as enabling technologies for microwave photonic filters.

We describe the use of various silicon photonic device technologies to implement microwave photonic filters (MPFs). We demonstrate four-wave mixing in a silicon nanowire waveguide (SNW) to increase the number of taps for MPFs based on finite impulse response filter designs. Using a 12 mm long SNW reduces the footprint by five orders of magnitude compared to silica highly nonlinear fiber while only requiring approximately two times more input power. We also demonstrate optical delays based on serial sidewall Bragg grating arrays and step-chirped sidewall Bragg gratings in silicon waveguides. We obtain up to 63 ps delay in discrete steps from 15 ps to 32 ps over a wide bandwidth range from 33 nm to at least 62 nm. These components can be integrated with other silicon-based components such as integrated spectral shapers and modulators to realize a fully integrated MPF.

On the precision of quasi steady state assumptions in stochastic dynamics.

Many biochemical networks have complex multidimensional dynamics and there is a long history of methods that have been used for dimensionality reduction for such reaction networks. Usually a deterministic mass action approach is used; however, in small volumes, there are significant fluctuations from the mean which the mass action approach cannot capture. In such cases stochastic simulation methods should be used. In this paper, we evaluate the applicability of one such dimensionality reduction method, the quasi-steady state approximation (QSSA) [L. Menten and M. Michaelis, "Die kinetik der invertinwirkung," Biochem. Z 49, 333369 (1913)] for dimensionality reduction in case of stochastic dynamics. First, the applicability of QSSA approach is evaluated for a canonical system of enzyme reactions. Application of QSSA to such a reaction system in a deterministic setting leads to Michaelis-Menten reduced kinetics which can be used to derive the equilibrium concentrations of the reaction species. In the case of stochastic simulations, however, the steady state is characterized by fluctuations around the mean equilibrium concentration. Our analysis shows that a QSSA based approach for dimensionality reduction captures well the mean of the distribution as obtained from a full dimensional simulation but fails to accurately capture the distribution around that mean. Moreover, the QSSA approximation is not unique. We have then extended the analysis to a simple bistable biochemical network model proposed to account for the stability of synaptic efficacies; the substrate of learning and memory [J. E. Lisman, "A mechanism of memory storage insensitive to molecular turnover: A bistable autophosphorylating kinase," Proc. Natl. Acad. Sci. U.S.A. 82, 3055-3057 (1985)]. Our analysis shows that a QSSA based dimensionality reduction method results in errors as big as two orders of magnitude in predicting the residence times in the two stable states.

Mapping the environmental fitness landscape of a synthetic gene circuit.

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a "sweet spot" of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings.

Linearizer gene circuits with negative feedback regulation.

Gene functional studies consist of phenotyping cells with altered gene expression. Improving the precision of current gene expression control techniques would enable more detailed studies of gene function. Here, we provide protocols for building synthetic gene constructs for tuning the expression of a gene in all the cells of a population precisely and uniformly, achieving expression levels proportional to the extracellular inducer concentration.

A common repressor pool results in indeterminacy of extrinsic noise.

For just over a decade, stochastic gene expression has been the focus of many experimental and theoretical studies. It is now widely accepted that noise in gene expression can be decomposed into extrinsic and intrinsic components, which have orthogonal contributions to the total noise. Intrinsic noise stems from the random occurrence of biochemical reactions and is inherent to gene expression. Extrinsic noise originates from fluctuations in the concentrations of regulatory components or random transitions in the cell's state and is imposed to the gene of interest by the intra- and extra-cellular environment. The basic assumption has been that extrinsic noise acts as a pure input on the gene of interest, which exerts no feedback on the extrinsic noise source. Thus, multiple copies of a gene would be uniformly influenced by an extrinsic noise source. Here, we report that this assumption falls short when multiple genes share a common pool of a regulatory molecule. Due to the competitive utilization of the molecules existing in this pool, genes are no longer uniformly influenced by the extrinsic noise source. Rather, they exert negative regulation on each other and thus extrinsic noise cannot be determined by the currently established method.

Tuning and controlling gene expression noise in synthetic gene networks.

Synthetic gene networks can be used to control gene expression and cellular phenotypes in a variety of applications. In many instances, however, such networks can behave unreliably due to gene expression noise. Accordingly, there is a need to develop systematic means to tune gene expression noise, so that it can be suppressed in some cases and harnessed in others, e.g. in cellular differentiation to create population-wide heterogeneity. Here, we present a method for controlling noise in synthetic eukaryotic gene expression systems, utilizing reduction of noise levels by TATA box mutations and noise propagation in transcriptional cascades. Specifically, we introduce TATA box mutations into promoters driving TetR expression and show that these mutations can be used to effectively tune the noise of a target gene while decoupling it from the mean, with negligible effects on the dynamic range and basal expression. We apply mathematical and computational modeling to explain the experimentally observed effects of TATA box mutations. This work, which highlights some important aspects of noise propagation in gene regulatory cascades, has practical implications for implementing gene expression control in synthetic gene networks.

Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression.

Although several recent studies have focused on gene autoregulation, the effects of negative feedback (NF) on gene expression are not fully understood. Our purpose here was to determine how the strength of NF regulation affects the characteristics of gene expression in yeast cells harboring chromosomally integrated transcriptional cascades that consist of the yEGFP reporter controlled by (i) the constitutively expressed tetracycline repressor TetR or (ii) TetR repressing its own expression. Reporter gene expression in the cascade without feedback showed a steep (sigmoidal) dose-response and a wide, nearly bimodal yEGFP distribution, giving rise to a noise peak at intermediate levels of induction. We developed computational models that reproduced the steep dose-response and the noise peak and predicted that negative autoregulation changes reporter expression from bimodal to unimodal and transforms the dose-response from sigmoidal to linear. Prompted by these predictions, we constructed a "linearizer" circuit by adding TetR autoregulation to our original cascade and observed a massive (7-fold) reduction of noise at intermediate induction and linearization of dose-response before saturation. A simple mathematical argument explained these findings and indicated that linearization is highly robust to parameter variations. These findings have important implications for gene expression control in eukaryotic cells, including the design of synthetic expression systems.

Effect of encoder--decoder mismatch due to wavelength and time misalignments on the performance of two-dimensional wavelength--time optical code-division multiple access systems.

We examine the effects of encoder and decoder mismatch due to wavelength and time chip misalignments on the bit-error rate (BER) performance of two-dimensional (2D) wavelength--time optical code-division multiple access systems. We investigate several instances of misalignment in the desired user encoder and decoder as well as in the interfering user encoders. Our simulation methodology can be used to analyze any type of 2D wavelength--time code family as well as probability distribution for misalignment. For illustration purposes, we consider codes generated by use of the depth-first search algorithm and a Gaussian distribution for the misalignment. Our simulation results show that, in the case of a misalignment in either wavelength or time chip, the variance of the distribution for the misalignment must be below 0.01 for the corresponding degradation in the BER system's performance to be less than 1 order of magnitude compared with that when there is no mismatch between the encoders and decoders. The tolerances become even more strict when misalignments in both wavelength and time chips are considered. Furthermore, our results show that the effect of misalignment in wavelength (time chips) is the same regardless of the number of wavelengths (time chips) used in the codes.