Mechanisms driving persistent airway inflammation in chronic obstructive pulmonary disease (COPD) are incompletely understood. As secretory immunoglobulin A (SIgA) deficiency in small airways has been reported in COPD patients, we hypothesized that immunobarrier dysfunction resulting from reduced SIgA contributes to chronic airway inflammation and disease progression. Here we show that polymeric immunoglobulin receptor-deficient (pIgR−/−) mice, which lack SIgA, spontaneously develop COPD-like pathology as they age. Progressive airway wall remodelling and emphysema in pIgR−/− mice are associated with an altered lung microbiome, bacterial invasion of the airway epithelium, NF-κB activation, leukocyte infiltration and increased expression of matrix metalloproteinase-12 and neutrophil elastase. Re-derivation of pIgR−/− mice in germ-free conditions or treatment with the anti-inflammatory phosphodiesterase-4 inhibitor roflumilast prevents COPD-like lung inflammation and remodelling. These findings show that pIgR/SIgA deficiency in the airways leads to persistent activation of innate immune responses to resident lung microbiota, driving progressive small airway remodelling and emphysema.
Given the complexity of host-microbiota symbioses, scientists and philosophers are asking questions at new biological levels of hierarchical organization—what is a holobiont and hologenome? When should this vocabulary be applied? Are these concepts a null hypothesis for host-microbe systems or limited to a certain spectrum of symbiotic interactions such as host-microbial coevolution? Critical discourse is necessary in this nascent area, but productive discourse requires that skeptics and proponents use the same lexicon. For instance, critiquing the hologenome concept is not synonymous with critiquing coevolution, and arguing that an entity is not a primary unit of selection dismisses the fact that the hologenome concept has always embraced multilevel selection. Holobionts and hologenomes are incontrovertible, multipartite entities that result from ecological, evolutionary, and genetic processes at various levels. They are not restricted to one special process but constitute a wider vocabulary and framework for host biology in light of the microbiome.
Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called “omics,” are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov–Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.
Summary The Mauthner cell (M-cell) is a command-like neuron in teleost fish whose firing in response to aversive stimuli is correlated with short-latency escapes [1–3]. M-cells have been proposed as evolutionary ancestors of startle response neurons of the mammalian reticular formation , and studies of this circuit have uncovered important principles in neurobiology that generalize to more complex vertebrate models . The main excitatory input was thought to originate from multisensory afferents synapsing directly onto the M-cell dendrites . Here, we describe an additional, convergent pathway that is essential for the M-cell-mediated startle behavior in larval zebrafish. It is composed of excitatory interneurons called spiral fiber neurons, which project to the M-cell axon hillock. By in vivo calcium imaging, we found that spiral fiber neurons are active in response to aversive stimuli capable of eliciting escapes. Like M-cell ablations, bilateral ablations of spiral fiber neurons largely eliminate short-latency escapes. Unilateral spiral fiber neuron ablations shift the directionality of escapes and indicate that spiral fiber neurons excite the M-cell in a lateralized manner. Their optogenetic activation increases the probability of short-latency escapes, supporting the notion that spiral fiber neurons help activate M-cell-mediated startle behavior. These results reveal that spiral fiber neurons are essential for the function of the M-cell in response to sensory cues and suggest that convergent excitatory inputs that differ in their input location and timing ensure reliable activation of the M-cell, a feedforward excitatory motif that may extend to other neural circuits.
Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently available single-molecule imaging techniques, provides an avenue to interrogate the process of transcription and its dynamics in cells by quantifying the number of RNA polymerases engaged in the transcription of a gene (or equivalently the number of nascent RNAs) at a given moment in time. In this paper, we propose that measurements of the cell-to-cell variability in the number of nascent RNAs provide a mostly unexplored method for deciphering mechanisms of transcription initiation in cells. We propose a simple kinetic model of transcription initiation and elongation from which we calculate nascent RNA copy-number fluctuations. To demonstrate the usefulness of this approach, we test our theory against published nascent RNA data for twelve constitutively expressed yeast genes. Rather than transcription being initiated through a single rate limiting step, as it had been previously proposed, our single-cell analysis reveals the presence of at least two rate limiting steps. Surprisingly, half of the genes analyzed have nearly identical rates of transcription initiation, suggesting a common mechanism. Our analytical framework can be used to extract quantitative information about dynamics of transcription from single-cell sequencing data, as well as from single-molecule imaging and electron micrographs of fixed cells, and provides the mathematical means to exploit the quantitative power of these technologies.
Microorganisms often exhibit a history-dependent phenotypic response after exposure to a stimulus which can be imperative for proper function. However, cells frequently experience unexpected environmental perturbations that might induce phenotypic switching. How cells maintain phenotypic states in the face of environmental fluctuations remains an open question. Here, we use environmental perturbations to characterize the resilience of phenotypic states in a synthetic gene network near a critical transition. We find that far from the critical transition an environmental perturbation may induce little to no phenotypic switching, whereas close to the critical transition the same perturbation can cause many cells to switch phenotypic states. This loss of resilience was observed for perturbations that interact directly with the gene circuit as well as for a variety of generic perturbations-such as salt, ethanol, or temperature shocks-that alter the state of the cell more broadly. We obtain qualitatively similar findings in natural gene circuits, such as the yeast GAL network. Our findings illustrate how phenotypic memory can become destabilized by environmental variability near a critical transition.
Roux-en-Y gastric bypass (RYGB) is highly effective in reversing obesity and associated diabetes. Recent observations in humans suggest a contributing role of increased circulating bile acids in mediating such effects. Here we use a diet-induced obesity (DIO) mouse model and compare metabolic remission when bile flow is diverted through a gallbladder anastomosis to jejunum, ileum or duodenum (sham control). We find that only bile diversion to the ileum results in physiologic changes similar to RYGB, including sustained improvements in weight, glucose tolerance and hepatic steatosis despite differential effects on hepatic gene expression. Circulating free fatty acids and triglycerides decrease while bile acids increase, particularly conjugated tauro-β-muricholic acid, an FXR antagonist. Activity of the hepatic FXR/FGF15 signalling axis is reduced and associated with altered gut microbiota. Thus bile diversion, independent of surgical rearrangement of the gastrointestinal tract, imparts significant weight loss accompanied by improved glucose and lipid homeostasis that are hallmarks of RYGB.
The Mauthner cell (M-cell) is a command-like neuron in teleost fish whose firing in response to aversive stimuli is correlated with short-latency escapes [1, 2 and 3]. M-cells have been proposed as evolutionary ancestors of startle response neurons of the mammalian reticular formation , and studies of this circuit have uncovered important principles in neurobiology that generalize to more complex vertebrate models . The main excitatory input was thought to originate from multisensory afferents synapsing directly onto the M-cell dendrites . Here, we describe an additional, convergent pathway that is essential for the M-cell-mediated startle behavior in larval zebrafish. It is composed of excitatory interneurons called spiral fiber neurons, which project to the M-cell axon hillock. By in vivo calcium imaging, we found that spiral fiber neurons are active in response to aversive stimuli capable of eliciting escapes. Like M-cell ablations, bilateral ablations of spiral fiber neurons largely eliminate short-latency escapes. Unilateral spiral fiber neuron ablations shift the directionality of escapes and indicate that spiral fiber neurons excite the M-cell in a lateralized manner. Their optogenetic activation increases the probability of short-latency escapes, supporting the notion that spiral fiber neurons help activate M-cell-mediated startle behavior. These results reveal that spiral fiber neurons are essential for the function of the M-cell in response to sensory cues and suggest that convergent excitatory inputs that differ in their input location and timing ensure reliable activation of the M-cell, a feedforward excitatory motif that may extend to other neural circuits.
Recently developed lab-on-a-chip technologies integrate multiple traditional assays on a single chip with higher sensitivity, faster assay time, and more streamlined sample operation. We discuss the prospects of the lab-on-a-tip platform, where assays can be integrated on a miniaturized tip for in situ and in vivo analysis. It will resolve some of the limitations of available lab-on-a-chip platforms and enable next generation multifunctional in vivo sensors, as well as analytical techniques at the single cell or even sub-cellular levels
Optical cavities that are capable for detecting single nanoparticles could lead to great progress in early stage disease diagnostics and the study of biological interactions on the single-molecule level. In particular, photonic crystal(PhC)cavities are excellent platforms for label-free single-nanoparticle detection, owing to their high quality (Q) factors and wavelength-scale modal volumes. Here, we demonstrate the design and fabrication of a high-Q (>104) slot-mode PhC nanobeam cavity, which is able to strongly confine light in the slotted regions. The enhanced light-matter interaction results in an order of magnitude improvement in both refractive index sensitivity (439 nm/RIU) and single-nanoparticle sensitivity compared with conventional dielectric-mode PhCcavities. Detection of single polystyrene nanoparticles with radii of 20 nm and 30 nm is demonstrated in aqueous environments (D2O), without additional laser and temperature stabilization techniques.
We report exceptionally low thresholds (9.1 μJ/cm2) for room temperature lasing at ∼450 nm in optically pumped Gallium Nitride(GaN) nanobeam cavity structures. The nanobeam cavity geometry provides high theoretical Q (>100 000) with small modal volume, leading to a high spontaneous emission factor, β = 0.94. The active layer materials are IndiumGallium Nitride(InGaN) fragmented quantum wells (fQWs), a critical factor in achieving the low thresholds, which are an order-of-magnitude lower than obtainable with continuous QWactive layers. We suggest that the extra confinement of photo-generated carriers for fQWs (compared to QWs) is responsible for the excellent performance.
Book description: At long last, here is the thoroughly revised and updated, and long-anticipated, third edition of the hugely successful Art of Electronics. Widely accepted as the best single authoritative text on electronic circuit design, it will be an indispensable reference and the gold standard for anyone in the field.
Weakly-scattering objects, such as small colloidal particles and most biological cells, are frequently encountered in microscopy. Indeed, a range of techniques have been developed to better visualize these phase objects; phase contrast and DIC are among the most popular methods for enhancing contrast. However, recording position and shape in the out-of-imaging-plane direction remains challenging. This report introduces a simple experimental method to accurately determine the location and geometry of objects in three dimensions, using digital inline holographic microscopy (DIHM). Broadly speaking, the accessible sample volume is defined by the camera sensor size in the lateral direction, and the illumination coherence in the axial direction. Typical sample volumes range from 200 µm x 200 µm x 200 µm using LED illumination, to 5 mm x 5 mm x 5 mm or larger using laser illumination. This illumination light is configured so that plane waves are incident on the sample. Objects in the sample volume then scatter light, which interferes with the unscattered light to form interference patterns perpendicular to the illumination direction. This image (the hologram) contains the depth information required for three-dimensional reconstruction, and can be captured on a standard imaging device such as a CMOS or CCD camera. The Rayleigh-Sommerfeld back propagation method is employed to numerically refocus microscope images, and a simple imaging heuristic based on the Gouy phase anomaly is used to identify scattering objects within the reconstructed volume. This simple but robust method results in an unambiguous, model-free measurement of the location and shape of objects in microscopic samples.
Swimming bacteria explore their environment by performing a random walk, which is biased in response to, for example, chemical stimuli, resulting in a collective drift of bacterial populations towards ‘a better life’. This phenomenon, called chemotaxis, is one of the best known forms of collective behaviour in bacteria, crucial for bacterial survival and virulence. Both single-cell and macroscopic assays have investigated bacterial behaviours. However, theories that relate the two scales have previously been difficult to test directly. We present an image analysis method, inspired by light scattering, which measures the average collective motion of thousands of bacteria simultaneously. Using this method, a time-varying collective drift as small as 50 nm s−1 can be measured. The method, validated using simulations, was applied to chemotactic Escherichia colibacteria in linear gradients of the attractant α-methylaspartate. This enabled us to test a coarse-grained minimal model of chemotaxis. Our results clearly map the onset of receptor methylation, and the transition from linear to logarithmic sensing in the bacterial response to an external chemoeffector. Our method is broadly applicable to problems involving the measurement of collective drift with high time resolution, such as cell migration and fluid flows measurements, and enables fast screening of tactic behaviours.
It is widely believed that the swimming speed, v, of many flagellated bacteria is a nonmonotonic function of the concentration, c, of high-molecular-weight linear polymers in aqueous solution, showing peaked v(c) curves. Pores in the polymer solution were suggested as the explanation. Quantifying this picture led to a theory that predicted peaked v(c) curves. Using high-throughput methods for characterizing motility, we measured v and the angular frequency of cell body rotation, Ω, of motile Escherichia coli as a function of polymer concentration in polyvinylpyrrolidone (PVP) and Ficoll solutions of different molecular weights. We find that nonmonotonic v(c) curves are typically due to low-molecular-weight impurities. After purification by dialysis, the measured v(c) and Ω(c) relations for all but the highest-molecular-weight PVP can be described in detail by Newtonian hydrodynamics. There is clear evidence for non-Newtonian effects in the highest-molecular-weight PVP solution. Calculations suggest that this is due to the fast-rotating flagella seeing a lower viscosity than the cell body, so that flagella can be seen as nano-rheometers for probing the non-Newtonian behavior of high polymer solutions on a molecular scale.
Ecosystems can undergo sudden shifts to undesirable states, but recent studies with simple single-species ecosystems have demonstrated that advance warning can be provided by the slowing down of population dynamics near a tipping point. However, it is unclear how this ‘critical slowing down’ will manifest in ecosystems with strong interactions between their components. Here we probe the dynamics of an experimental producer-freeloader ecosystem as it approaches a catastrophic collapse. Surprisingly, the producer population grows in size as the environment deteriorates, highlighting that population size can be a misleading measure of ecosystem stability. By analysing the oscillatory producer-freeloader dynamics for over 100 generations in multiple environmental conditions, we find that the collective ecosystem dynamics slow down as the tipping point is approached. Analysis of the coupled dynamics of interacting populations may therefore be necessary to provide advance warning of collapse in complex communities.
Spatial tailoring of the material constitutive properties is a well-known strategy to mold the local flow of given observables in different physical domains. Coordinate-transformation-based methods (e.g., trans-formation optics) offer a powerful and systematic approach to design anisotropic, spatially inhomogeneous artificial materials (metamaterials) capable of precisely manipulating wave-based (electromagnetic, acoustic, elastic) as well as diffusion-based (heat) phenomena in a desired fashion. However, as versatile as these approaches have been, most designs have thus far been limited to serving single-target functionalities in a given physical domain. Here, we present a step towards a “transformation multiphysics” framework that allows independent and simultaneous manipulation of multiple physical phenomena. As a proof of principle of this new scheme, we design and synthesize (in terms of realistic material constituents) a metamaterial shell that simultaneously behaves as a thermal concentrator and an electrical “invisibility cloak.” Our numerical results open up intriguing possibilities in the largely unexplored phase space of multifunctional metadevices, with a wide variety of potential applications to electrical, magnetic, acoustic, and thermal scenarios.
Digital cameras would be colorblind if they did not have pixelated color filters integrated into their image sensors. Integration of conventional fixed filters, however, comes at the expense of an inability to modify the camera’s spectral properties. Instead, we demonstrate a micropolarizer-based camera that can reconfigure its spectral response. Color is encoded into a linear polarization state by a chiral dispersive element and then read out in a single exposure. The polarization encoded color camera is capable of capturing three-color images at wavelengths spanning the visible to the near infrared.