Gut microbial community supplementation and reduction modulates African armyworm susceptibility to a baculovirus

Gut microbiota stimulates the immune system and inhibits pathogens, and thus, it is critical for disease prevention. Probiotics represent an effective alternative to antibiotics used for the therapy and prevention of bacterial diseases. Probiotic bacteria are commonly used in vertebrates, although their use in invertebrates is still rare. We manipulated the gut microbiome of the African Armyworm (Spodoptera exempta Walker) using antibiotics and field-collected frass, in an attempt to understand the interactions of the gut microbiome with the nucleopolyhedrovirus, SpexNPV. We found that S. exempta individuals with supplemented gut microbiome were significantly more resistant to SpexNPV, relative to those with a typical laboratory gut microbiome. Illumina MiSeq sequencing revealed the bacterial phyla in the S. exempta gut belonged to 28 different classes. Individuals with an increased abundance of Lactobacillales had a higher probability of surviving viral infection. In contrast, there was an increased abundance of Enterobacteriales and Pseudomonadales in individuals dying from viral infection, corresponding with decreased abundance of these two Orders in surviving caterpillars, suggesting a potential role for them in modulating the interaction between the host and its pathogen. These results have important implications for laboratory studies testing biopesticides

Antimicrobial Resistance in Neisseria gonorrhoeae: Proceedings of the STAR Sexually Transmitted Infection-Clinical Trial Group Programmatic Meeting.

The goal of the Sexually Transmitted Infection Clinical Trial Group's Antimicrobial Resistance (AMR) in Neisseria gonorrhoeae (NG) meeting was to assemble experts from academia, government, nonprofit and industry to discuss the current state of research, gaps and challenges in research and technology and priorities and new directions to address the continued emergence of multidrug-resistant NG infections. Topics discussed at the meeting, which will be the focus of this article, include AMR NG global surveillance initiatives, the use of whole genome sequencing and bioinformatics to understand mutations associated with AMR, mechanisms of AMR, and novel antibiotics, vaccines and other methods to treat AMR NG. Key points highlighted during the meeting include: (i) US and International surveillance programs to understand AMR in NG; (ii) the US National Strategy for combating antimicrobial-resistant bacteria; (iii) surveillance needs, challenges, and novel technologies; (iv) plasmid-mediated and chromosomally mediated mechanisms of AMR in NG; (v) novel therapeutic (eg, sialic acid analogs, factor H [FH]/Fc fusion molecule, monoclonal antibodies, topoisomerase inhibitors, fluoroketolides, LpxC inhibitors) and preventative (eg, peptide mimic) strategies to combat infection. The way forward will require renewed political will, new funding initiatives, and collaborations across academic and commercial research and public health programs

The Ursinus Weekly, October 10, 1969

Seven join, six leave Ursinus faculty • UC and 500 colleges schedule Vietnam moratorium Wednesday; Classes not officially cancelled • William D. Reimert dies, Ursinus Board President • Dr. E. Lewis\u27 math textbook aids Ursinus blind students • Pre-Med convention • Dean Harris weds Bryn Mawr man • Editorial: A very good year • Focus: Mike Stoner in exile • Compulsory convocation: Its validity and purpose • New view of Ursinus • Dr. Rice endorses Vietnam moratorium • Kitchen cynic: Suppose U.C. had mandatory convocations • Perspectives • To eat or not to eat • Board names new members • Spotlight: Mr. Jones, cook • Centennial plans • Opinion: Suggestions for revision of the school calendar • Weaver raps • Faculty portrait: Mrs. Lucas • Woodstock vs. Ursinus • Essay on the new age • Building plans • Freshman class • Harriers extend streak to 26 • Shuman, Mangan potential greats • Flying Dutchmen edge Bears on late T.D. • Ursinus drops grid opener to Diplomats • Registration system analyzed • Lack of needed funds signals impending collapse of agency • Astronaut Scott Carpenter opens Fall Forum series • Ursinus accounting students rank first twice, and secondhttps://digitalcommons.ursinus.edu/weekly/1149/thumbnail.jp

General Framework for Meta-Analysis of Haplotype Association Tests

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.Generation Scotland: Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6 and the Scottish Funding Council HR03006. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland, and was funded by the UKâs Medical Research Council. Ethics approval for the study was given by the NHS Tayside committee on research ethics (reference 05/S1401/89). We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants and nurses. FamHS: Family Heart Study was supported by NIH grants RO1-HL-087700 and RO1-HL-088215 (M.A.P., PI) from NHLBI, and RO1-DK-8925601 and RO1-DK-075681 (I.B.B., PI) from NIDDK. MESA: MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-001079, and UL1-TR-000040. Funding for SHARe genotyping was provided by NHLBI contract N02-HL-64278. Funding for MESA Family was provided by grants R01-HL-071051, R01-HL-071205, R01-HL-071250, R01-HL-071251, R01-HL-071252, R01-HL-071258, R01-HL-071259, and UL1-RR-025005. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. FHS: Framingham Heart Study—Genotyping, quality control, and calling of the Illumina HumanExome BeadChip in the Framingham Heart Study was supported by funding from the National Heart, Lung and Blood Institute, Division of Intramural Research (Daniel Levy and Christopher J. OâDonnell, Principle Investigators). A portion of this research was conducted using the Linux Clusters for Genetic Analysis (LinGA) computing resources at Boston University Medical Campus. Also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616, NIDDK K24 DK080140, and American Diabetes Association Mentor-Based Postdoctoral Fellowship Award #7-09-MN-32, all to Dr. Meigs. FENLAND: The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team, and the Epidemiology Field, Data and Laboratory teams. EPIC-Potsdam: We thank all EPIC-Potsdam participants for their invaluable contribution to the study. The study was supported in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.). The recruitment phase of the EPIC-Potsdam study was supported by the Federal Ministry of Science, Germany (01 EA 9401) and the European Union (SOC 95201408 05 F02). The follow-up of the EPIC-Potsdam study was supported by German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05 F02). Furthermore, we thank Dr. Manuela Bergmann who was responsible for the methodological and organizational work of data collections of exposures and outcomes and Wolfgang Fleischhauer for his medical expertise that was employed in case ascertainment and contacts with the physicians and Ellen Kohlsdorf for data management. CHS: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL103612, HL068986 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/gepi.2195

Soil sedimentology at Gusev Crater from Columbia Memorial Station to Winter Haven

A total of 3140 individual particles were examined in 31 soils along Spirit’s traverse. Their size, shape, and texture were quantified and classified. They represent a unique record of 3 years of sedimentologic exploration from landing to sol 1085 covering the Plains Unit to Winter Haven where Spirit spent the Martian winter of 2006. Samples in the Plains Unit and Columbia Hills appear as reflecting contrasting textural domains. One is heterogeneous, with a continuum of angular-to-round particles of fine sand to pebble sizes that are generally dust covered and locally cemented in place. The second shows the effect of a dominant and ongoing dynamic aeolian process that redistributes a uniform population of medium-size sand. The texture of particles observed in the samples at Gusev Crater results from volcanic, aeolian, impact, and water-related processes

General Framework for Meta-Analysis of Haplotype Association Tests.

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.Generation Scotland: Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6 and the Scottish Funding Council HR03006. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland, and was funded by the UKâs Medical Research Council. Ethics approval for the study was given by the NHS Tayside committee on research ethics (reference 05/S1401/89). We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants and nurses. FamHS: Family Heart Study was supported by NIH grants RO1-HL-087700 and RO1-HL-088215 (M.A.P., PI) from NHLBI, and RO1-DK-8925601 and RO1-DK-075681 (I.B.B., PI) from NIDDK. MESA: MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-001079, and UL1-TR-000040. Funding for SHARe genotyping was provided by NHLBI contract N02-HL-64278. Funding for MESA Family was provided by grants R01-HL-071051, R01-HL-071205, R01-HL-071250, R01-HL-071251, R01-HL-071252, R01-HL-071258, R01-HL-071259, and UL1-RR-025005. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. FHS: Framingham Heart Study—Genotyping, quality control, and calling of the Illumina HumanExome BeadChip in the Framingham Heart Study was supported by funding from the National Heart, Lung and Blood Institute, Division of Intramural Research (Daniel Levy and Christopher J. OâDonnell, Principle Investigators). A portion of this research was conducted using the Linux Clusters for Genetic Analysis (LinGA) computing resources at Boston University Medical Campus. Also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616, NIDDK K24 DK080140, and American Diabetes Association Mentor-Based Postdoctoral Fellowship Award #7-09-MN-32, all to Dr. Meigs. FENLAND: The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team, and the Epidemiology Field, Data and Laboratory teams. EPIC-Potsdam: We thank all EPIC-Potsdam participants for their invaluable contribution to the study. The study was supported in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.). The recruitment phase of the EPIC-Potsdam study was supported by the Federal Ministry of Science, Germany (01 EA 9401) and the European Union (SOC 95201408 05 F02). The follow-up of the EPIC-Potsdam study was supported by German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05 F02). Furthermore, we thank Dr. Manuela Bergmann who was responsible for the methodological and organizational work of data collections of exposures and outcomes and Wolfgang Fleischhauer for his medical expertise that was employed in case ascertainment and contacts with the physicians and Ellen Kohlsdorf for data management. CHS: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL103612, HL068986 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/gepi.2195