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Microorganisms have coevolved diverse mechanisms to impair host defenses. A major one, superantigens, can result in devastating effects on the immune system. While all known superantigens induce vast immune cell proliferation and come from opportunistic pathogens, recently, proteins with similar broad specificity to antibody variable (V) domain families were identified in a commensal microbiota. These proteins, identified in the human commensal Ruminococcus gnavus, are called immunoglobulin-binding protein (Ibp) A and B and have been shown to activate B cells in vitro expressing either human VH3 or murine VH5/6/7. Here, we provide molecular and functional studies revealing the basis of this Ibp/immunoglobulin (Ig) interaction. The crystal structure and biochemical assays of a truncated IbpA construct in complex with mouse VH5 antigen-binding fragment (Fab) shows a binding of Ig heavy chain framework residues to the Ibp Domain D and the C-terminal heavy chain binding domain (HCBD). We used targeted mutagenesis of contact residues and affinity measurements and performed studies of the Fab-IbpA complex to determine the stoichiometry between Ibp and VH domains, suggesting Ibp may serve to cluster full-length IgA antibodies in vivo. Furthermore, in vitro stimulation experiments indicate that binding of the Ibp HCBD alone is sufficient to activate responsive murine B cell receptors. The presence of these proteins in a commensal microbe suggest that binding a broad repertoire of immunoglobulins, particularly in the gut/microbiome environment, may provide an important function in the maintenance of host/microbiome homeostasis contrasting with the pathogenic role of structurally homologous superantigens expressed by pathogens.

Spironolactone, a potassium-sparing diuretic and aldosterone antagonist, is a mineralocorticoid hormone commonly prescribed to patients suffering from heart failure, hirsutism, dermatological afflictions, and hypertension. Interestingly, relatively little work has been done on the development of vertebrate embryos after exposure to this compound. Here, we treat zebrafish embryos with spironolactone at 10

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain., eLife digest Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain.

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions.Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

The concentrations of 3,4-dihydroxybenzoic acid, caffeic acid, catechin, chlorogenic acid, epicatechin, gallic acid, p-coumaric acid, quercetin, rutin, ferulic acid, and the major metals in graviola (Annona muricata), atemoya (A. squamosa x A. cherimola), fruta do conde (A. squamosa), biribá (Rollinia mucosa), and the North American pawpaw (Asimina triloba) were determined by UPLC-ESI (-)-MS/MS. It enabled the identification and quantification of phenolic compounds. Catechin was only found in atemoya, at a concentration of 38.6 μg/g-dw. Only 3,4-dihydroxybenzoic acid was found in the fruit pulps of all five fruits analyzed. Atemoya stands out for not only having catechin but also for having much more epicatechin (239 μg/g-dw) than the other fruits. At the same time, graviola had more p-coumaric acid (62.6 μg/g-dw), and the North American pawpaw had more chlorogenic acid (48.1 μg/g-dw) than the other fruits. Metals were determined by ICP equipped with axially viewed plasma. All five fruit pulps had relatively high levels of potassium, with concentrations ranging from 7640 to 15,000 μg/g-dw, with pawpaw being the lowest and atemoya being the highest. The concentrations of other metals ranged from Ca 547 to 1110, Na 14.3 to 123, P 1210 to 1690, Mg 472 to 980, Mn 1.86 to 5.27, and Zn 5.55 to 7.32 μg/g-dw. All five fruits in the Annonaceae family that were analyzed in this study have several phenolic compounds in them and were good sources of potassium, calcium, phosphorus, and magnesium.

Cell shape changes such as cytokinesis are driven by the actomyosin contractile cytoskeleton. The molecular rearrangements that bring about contractility in nonmuscle cells are currently debated. Specifically, both filament sliding by myosin motors, as well as cytoskeletal cross-linking by myosins and nonmotor cross-linkers, are thought to promote contractility. Here we examined how the abundance of motor and nonmotor cross-linkers affects the speed of cytokinetic furrowing. We built a minimal model to simulate contractile dynamics in the Caenorhabditis elegans zygote cytokinetic ring. This model predicted that intermediate levels of nonmotor cross-linkers are ideal for contractility; in vivo, intermediate levels of the scaffold protein anillin allowed maximal contraction speed. Our model also demonstrated a nonlinear relationship between the abundance of motor ensembles and contraction speed. In vivo, thorough depletion of nonmuscle myosin II delayed furrow initiation, slowed F-actin alignment, and reduced maximum contraction speed, but partial depletion allowed faster-than-expected kinetics. Thus, cytokinetic ring closure is promoted by moderate levels of both motor and nonmotor cross-linkers but attenuated by an over-abundance of motor and nonmotor cross-linkers. Together, our findings extend the growing appreciation for the roles of cross-linkers in cytokinesis and reveal that they not only drive but also brake cytoskeletal remodeling.

Cytokinesis and other cell shape changes are driven by the actomyosin contractile cytoskeleton. The molecular rearrangements that bring about contractility in non-muscle cells are currently debated. Specifically, both filament sliding by myosin motors, as well as cytoskeletal crosslinking by myosins and non-motor crosslinkers, are thought to promote contractility. Here, we examined how the abundance of motor and non-motor crosslinkers controls the speed of cytokinetic furrowing. We built a minimal model to simulate the contractile dynamics of the C. elegans zygote cytokinetic ring. This model predicted that intermediate levels of non-motor crosslinkers would allow maximal contraction speed, which we found to be the case for the scaffold protein anillin, in vivo. Our model also demonstrated a non-linear relationship between the abundance of motor ensembles and contraction speed. In vivo, thorough depletion of non-muscle myosin II delayed furrow initiation, slowed F-actin alignment, and reduced maximum contraction speed, but partial depletion allowed faster-than-expected kinetics. Thus, both motor and non-motor crosslinkers promote cytokinetic ring closure when present at low levels, but act as a brake when present at higher levels. Together, our findings extend the growing appreciation for the roles of crosslinkers, but reveal that they not only drive but also brake cytoskeletal remodeling.

In this chapter, several different sample preparation techniques and analytical methods are described in order to analyze 16 elements determined in the Total Diet Study (TDS). The concentrations of these elements found in TDS samples vary from parts per billion to parts per hundred (percent). A variety of sample preparation techniques are described consisting of the digestion of these samples by various mixtures of acids or the direct oxidation of organic matter via ashing of these samples in a muffle furnace. A variety of instruments are used for the determination of the elements of interest including inductively coupled plasma atomic emission spectrophotometers, atomic absorption spectrophotometers (heated graphite furnace and hydride generation techniques), ultraviolet-visible spectrometers, and a direct reading mercury analyzer. These topics are all briefly addressed in this chapter.

A model system was used to cook wheat flour and water dough pieces in sealed pressure tubes under controlled pH conditions and with various additives in the recipe water to determine acrylamide (AA) formation and elimination. The potential effectiveness of calcium as CaCl2 or CaCO3 salts to reduce the formation of AA in wheat based food products was assessed. Since the divalent Ca2+ was capable of inducing significant pH reduction in the dough, and pH lowering is known to reduce AA formation, it was necessary in some cases to adjust the pH before cooking or use a pH matched control. For comparison, the effect of NaCl on AA formation was also determined. It was found that AA reduction up to 36% was obtained by adding CaCl2 to the recipe water at a 0.04 M concentration, compared to 23% for 0.04 M NaCl, and there was no reduction when CaCO3 was added to simulate a calcium enriched flour.