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Tumor suppressor genes (TSGs) are often involved in maintaining homeostasis. Loss of tumor suppressor functions causes cellular plasticity that drives numerous types of cancer, including small-cell lung cancer (SCLC), an aggressive type of lung cancer. SCLC is largely driven by numerous loss-of-function mutations in TSGs, often in those encoding chromatin modifiers. These mutations present a therapeutic challenge because they are not directly actionable. Alternatively, understanding the resulting molecular changes may provide insight into tumor intervention strategies. We hypothesize that despite the heterogeneous genomic landscape in SCLC, the impacts of mutations in patient tumors are related to a few important pathways causing malignancy. Specifically, alterations in chromatin modifiers result in transcriptional dysregulation, driving mutant cells toward a highly plastic state that renders them immune evasive and highly metastatic. This review will highlight studies in which imbalance of chromatin modifiers with opposing functions led to loss of immune recognition markers, effectively masking tumor cells from the immune system. This review also discusses the role of chromatin modifiers in maintaining neuroendocrine characteristics and the role of aberrant transcriptional control in promoting epithelial-to-mesenchymal transition during tumor development and progression. While these pathways are thought to be disparate, we highlight that the pathways often share molecular drivers and mediators. Understanding the relationships among frequently altered chromatin modifiers will provide valuable insights into the molecular mechanisms of SCLC development and progression and therefore may reveal preventive and therapeutic vulnerabilities of SCLC and other cancers with similar mutations.

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.

SUMMARY Human rhinoviruses cause the common cold and exacerbate chronic respiratory diseases. Although infection elicits neutralizing antibodies, these do not persist or cross-protect across multiple rhinovirus strains. To analyze rhinovirus-specific B cell responses in humans, we developed techniques using intact RV-A16 and RV-A39 for high-throughput high-dimensional single-cell analysis, with parallel assessment of antibody isotypes in an experimental infection model. Our approach identified T-bet+ B cells binding both viruses that account for ~5% of CXCR5− memory B cells. These B cells infiltrate nasal tissue and expand in the blood after infection. Their rapid secretion of heterotypic immunoglobulin G (IgG) in vitro, but not IgA, matches the nasal antibody profile post-infection. By contrast, CXCR5+ memory B cells binding a single virus are clonally distinct, absent in nasal tissue, and secrete homotypic IgG and IgA, mirroring the systemic response. Temporal and spatial functions of dichotomous memory B cells might explain the ability to resolve infection while rendering the host susceptible to re-infection., In Brief Eccles et al. demonstrate a key role for T-bet+ B cells in rapid local cross-reactive immunoglobulin G (IgG) responses to rhinovirus, whereas strain-specific B cells that are phenotypically distinct match systemic antibodies found later. This might explain efficient clearance of virus in the acute phase but narrow protection and continued susceptibility after the infection clears., Graphical Abstract

We screened 615 gram-positive isolates from 150 healthy children for the presence of the erm (A), erm (B), erm (C), erm (F), and mef (A) genes. The mef (A) genes were found in 20 (9%) of the macrolide-resistant isolates, including Enterococcus spp., Staphylococcus spp., and Streptococcus spp. Sixteen of the 19 gram-positive isolates tested carried the other seven open reading frames (ORFs) described in Tn 1207.1 , a genetic element carrying mef (A) recently described in Streptococcus pneumoniae . The three Staphylococcus spp. did not carry orf1 to orf3 . A gram-negative Acinetobacter junii isolate also carried the other seven ORFs described in Tn 1207.1. A Staphylococcus aureus isolate, a Streptococcus intermedius isolate, a Streptococcus sp. isolate, and an Enterococcus sp. isolate had their mef (A) genes completely sequenced and showed 100% identity at the DNA and amino acid levels with the mef (A) gene from S. pneumoniae .

Escherichia coli O157:H7 is rare yet widely distributed within bovine populations, where it is a benign commensal of the gastrointestinal tract (3). Most E. coli O157:H7-related human illness has been the result of contamination of meat, other foodstuffs, and/or drinking water with bovine wastes containing this organism (Division of Bacterial and Mycotic Diseases, Centers for Disease Control and Prevention, Escherichia coli O157:H7 [http://www.cdc.gov/ncidod/dbmd/diseaseinfo/escherichiacoli_g.htm]). In humans, E. coli O157:H7 may cause no symptoms, mild to severe diarrhea, hemorrhagic colitis, or hemolytic-uremic syndrome (11; http://www.cdc.gov/ncidod/dbmd/diseaseinfo/escherichiacoli_g.htm). As previously reported, an increase in antibiotic resistance has been noted within E. coli O157:H7 populations over the last 20 years (3, 4, 10). Testing of susceptibility to 12 different antibiotics and antibiotic combinations was performed on 901 randomly selected E. coli O157:H7 isolates collected between 1997 and 2000 from our collection. This included 663 bovine isolates from feedlots in the midwestern United States and 238 human isolates, which represented both outbreaks and sporadic cases, from public health departments of Washington, Oregon, Nevada, Wisconsin, Georgia, and Illinois. Isolates were verified as E. coli O157:H7 by being plated on sorbitol MacConkey agar (Becton Dickinson, Sparks, Md.), followed by a latex agglutination test (Oxoid, Basingstoke, Hampshire, United Kingdom). Disk diffusion assays were done using the National Committee for Laboratory Standards protocol and the control E. coli strain ATCC 25922 (7). The following antibiotic disks were used: ampicillin (10 μg), ampicillin-sulbactam (10 and 10 μg, respectively), ceftriaxone (30 μg), nalidixic acid (30 μg), ciprofloxacin (5 μg), kanamycin (30 μg), gentamicin (10 μg), amikacin (30 μg), streptomycin (10 μg), tetracycline (30 μg), and trimethoprim-sulfamethoxazole (1.25 and 23.75 μg, respectively). Antibiotic disks were supplied by Becton Dickinson Microbiology Systems (Franklin Lakes, N.J.). Forty-four (6.6%) bovine isolates and 29 (12.2%) human isolates were resistant to one or more antibiotics. Tetracycline resistance (Tcr) was the most common resistance found, with 43 of 44 (98%) resistant bovine isolates and 15 of 29 (52%) resistant human isolates being tetracycline resistant. Streptomycin resistance was found in 29 (66%) resistant bovine isolates and 13 (45%) resistant human isolates. Ampicillin was the third most common resistance phenotype with four (9%) of the resistant bovine isolates and eight (27%) of the resistant human isolates being ampicillin resistant. Thirty (68%) of the resistant bovine isolates and 15 (52%) of the resistant human isolates were multidrug resistant, defined as resistance to two or more different classes of antibiotics such as tetracycline and ampicillin. These results are similar to those of Kim et al. (4), who reported 13 of 176 (7.4%) isolates collected between 1989 and 1991 to be resistant to streptomycin, sulfisoxazole, and tetracycline. Schroeder et al. (10) also found similar results with 5% of 85 human isolates being ampicillin resistant and 11% of 93 cow isolates being tetracycline resistant among isolates collected between 1985 and 2002. In contrast, Galland et al. (3) found 10 (38.5%) isolates resistant to tetracycline and 2 (7.7%) resistant to ampicillin from 26 cattle isolates of E. coli O157:H7. However, this group tested very few isolates, which may account for the differences found. The level of antibiotic resistance within E. coli O157:H7 from humans and bovines between 1997 and 2000 was lower than that traditionally found with other E. coli isolates; however the level of resistance appears stable compared to those found in other studies of resistance within O157:H7 (3, 4, 10). Previously the tet(A), tet(B), tet(C), tet(D), tet(E), and tet(G) genes have been identified in tetracycline-resistant E. coli strains (1, 2, 3, 4, 5, 6, 9). However, little is known about distribution among E. coli O157:H7 isolates from either humans or animals. Whole-bacterium dot blots were used to screen for the presence of the six genes as previously described (6, 8). The oligonucleotide sequence for each probe and the number of isolates carrying each gene are listed in Table ​Table11. TABLE 1. Primers used for DNA-DNA hybridization of tetracycline resistance determinants and distribution of tetracycline genes by host Sixty percent of the Tcr strains carried the tet(B) gene, which was the most prevalent tet gene found (Table ​(Table1).1). In a previous study, of non-O157 E. coli strains, tet(B) was also the dominant gene and found in 80% of Tcr E. coli isolates (1). The tet(A) gene was found in four (10%) of the Tcr bovine isolates and three (20%) of the Tcr human isolates. The tet(C) gene was found in three (7%) of the Tcr bovine isolates and no human isolates. The tet(G) gene was found in one (2%) Tcr bovine isolate and three (20%) Tcr human isolates. The tet(D) and tet(E) genes were not found in any of the isolates. One Tcr bovine isolates and four Tcr human isolates carried two different tetracycline resistance genes, and one Tcr bovine isolate carried three different tet genes. Thirteen (31%) Tcr bovine isolates and three (20%) Tcr human isolates did not hybridize with any of the known genes examined. In preliminary analysis, none of the 16 isolates hybridized with the recently identified tet(Y) gene (9), suggesting that these strains either may carry one of the other known tet genes not previously identified in E. coli or may have a novel gene. To distinguish between these hypotheses, the other known efflux tet genes, the only type currently identified in E. coli, will need to be screened. The finding that 31% of the Tcr bovine isolates carried unidentified tetracycline resistance genes, in this study, is very similar to a recent report that 40% of the Tcr isolates from Chilean salmon farms (6) carried unidentified tetracycline resistance genes. The data from these two studies suggest that Tcr gram-negative bacteria taken from nonhuman animals and/or the environment carry a more diverse group of tetracycline resistance genes than are usually found when characterizing Tcr gram-negative bacteria from humans.