The objective of this study was to explore the R. microplus microbiome by applying the bacterial 16S tag-encoded FLX-titanium amplicon pyrosequencing (bTEFAP) technique to characterize its bacterial diversity. Pyrosequencing was performed on adult males and females, eggs, and gut and ovary tissues from adult females derived from samples of R. microplus collected during outbreaks in southern Texas. Raw data from bTEFAP were screened and trimmed based upon quality scores and binned into individual sample collections. Bacteria identified to the species level include Staphylococcus aureus, Staphylococcus chromogenes, Streptococcus dysgalactiae, Staphylococcus sciuri, Serratia marcescens, Corynebacterium glutamicum, and Finegoldia magna. One hundred twenty-one bacterial genera were detected in all the life stages and tissues sampled. The total number of genera identified by tick sample comprised: 53 in adult males, 61 in adult females, 11 in gut tissue, 7 in ovarian tissue, and 54 in the eggs. Notable genera detected in the cattle tick include Wolbachia, Coxiella, and Borrelia. The molecular approach applied in this study allowed us to assess the relative abundance of the microbiota associated with R. microplus. Ticks are regarded as the most relevant vectors of disease-causing pathogens in domestic and wild animals. The cattle tick, Rhipicephalus (Boophilus) microplus, hinders livestock production in tropical and subtropical parts of the world where it is endemic. Tick microbiomes remain largely unexplored.

Phytophthora rubi and P. fragariae are two closely related soil-borne oomycete plant pathogens that exhibit strong morphological and physiological similarities but are specialized to infect different hosts of economic importance, namely, raspberry and strawberry. Here, we report the draft genome sequences of these two Phytophthora species as a first step toward understanding the genomic processes underlying plant host adaptation in these pathogens.

FIB concentrations, rate of release from manure, FIB transport, daily flow, non-point source. This dataset is associated with the following publication: Kim, K., G. Whelan, M. Molina, R. Parmar, K. Wolfe, M. Galvin, P. Duda, R. Zepp, J. Kinzelman, G. Kleinheinz, and M. Borchardt. Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed-Use Watersheds. JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 47(5): 1103-1114, (2018).

FSIS calculates prevalence, volume weighted percent positive, or percent positive calculations for microbial pathogens in FSIS regulated products that are currently sampled through existing sampling projects. FSIS intends to provide new calculations each quarter using the prior 12 months of sampling data. See the FSIS website for additional information.

Fecal contamination of recreational waters with cattle manure can pose a risk to public health due to the potential presence of various zoonotic pathogens. Fecal indicator bacteria (FIB) have a long history of use in the assessment. However, FIB quantification provides no information about pollution sources. Microbial source tracking (MST) genetic markers have been developed in response to a need to identify pollution sources, yet factors that influence host-identifier target decay once discharged into the environment are often poorly understood, especially for agriculture fecal waste sources. Here, we investigate the influence of water type (freshwater versus marine) and select environmental parameters (indigenous microbiota, ambient sunlight) on the decay of FIB and MST genetic markers originating from cattle manure. Experiments were conducted in situ using a submersible aquatic mesocosm containing dialysis bags filled with a mixture of cattle manure and ambient water. Culturable FIB (E. coli and enterococci) were enumerated by membrane filtration and the concentration of general fecal indicator bacteria (GenBac3, Entero1a, and EC23S857) and MST (Rum2Bac, CowM2, and CowM3) genetic markers were estimated by qPCR. Water type was the most significant factor influencing the decay of cattle manure indicator bacteria (three-way ANOVA, p: 0.006 to < 0.001), although the magnitude of the effect differed among microbial targets and over time. The presence of indigenous microbiota and exposure to sunlight were both significantly correlated (three-way ANOVA, p: 0.044 to < 0.001) with decay of enterococci and CowM2, while E. coli, EC23S857, Rum2Bac, and CowM3 (three-way ANOVA, p: 0.044 <0.001) were significantly impacted by either sunlight or indigenous microbiota. Findings indicate the extended persistence (>144 hours) of both cultivated FIB and genetic markers in marine and freshwater water types. Findings suggest that multiple environmental stressors are important determinants of FIB and MST marker persistence, but their magnitude can vary across different indicators. Selective exclusion of natural aquatic microbiota and/or sunlight typically resulted in extended survival, but the effect was minor and limited to select microbial targets. This dataset is associated with the following publication: Korajkic, A., B. McMinn, N. Ashbolt, M. Sivaganesan, V. Harwood, and O. Shanks. Extended persistence of general and cattle-associated fecal indicators in marine and freshwater environment. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 650(1): 1292-1302, (2018).

Organisms living in honey bees and honey bee colonies form large associative holobiont communities that are integral to bee biology. High-throughput sequencing approaches to characterize these holobiont communities from honey bees in various states of health and disease are now commonplace, producing large amounts of nucleotide sequence data that must be accurately and consistently analyzed in order to produce reliable and comparable reports. In addition, new species designations and revisions are actively being made from honey bee holobiont communities, complicating nomenclature in larger databases where taxonomic descriptions associated with archived sequences can quickly become outdated and misleading. To improve the accuracy and consistency of honey bee holobiont research, we have developed HoloBee: a curated database of publicly accessioned nucleotide sequences from the honey bee holobiont community. Except in rare and noted exceptions made by curators, sequences used in HoloBee were obtained from, or in association with, Apis mellifera (Western honey bee) as well as other honey bee species where available (e.g. Apis cerana, Apis dorsata, Apis laboriosa, Apis koschevnikovi, Apis florea, Apis andreniformis and Apis nigrocincta). Sources include: within or on the surface of honey bees (adult, pupae, larvae, egg), corbicular pollen, bee bread, royal jelly, honey, comb, hive surfaces (e.g. bottom board debris, frames, landing platforms), and isolates of microbes, parasites and pathogens from honey bees. HoloBee contains two non-overlapping sets of sequence data, HoloBee-Barcode and HoloBee-Mop, each of which have distinct intended uses. HoloBee-Barcode is a non-redundant database of taxonomically informative barcoding loci for all viruses, bacteria, fungi, protozoans and metazoans associated with honey bees (Apis spp.). It was created from an exhaustive master sequence archive of all valid holobiont sequences. Redundancy was removed from this master archive using a clustering algorithm that grouped sequences with ≥ 99% identity and retained the longest sequence from each cluster as the representative accession for that sequence type (“centroid”). These centroid sequences were concatenated into a fasta formatted file to create the HoloBee-Barcode database. Associated taxonomy for each centroid, including Superkingdom through Species and Strain/Isolate, was individually reviewed and corrected when necessary by a curator. Cross reference tables (separated according to 5 major taxonomic groups) provide a user-friendly outline of information for each centroid accession within HoloBee-Barcode including taxonomy, gene/product name, sequence length, the unaltered NCBI definition line, the number and identity of redundant sequences clustered within each centroid, and any additional information provided by the curator. HoloBee-Barcode centroid counts are: Viruses = 86; Bacteria = 496; Fungi = 41; Protozoa = 4; Metazoa = 60. HoloBee-Barcode is intended to improve and standardize quantitative and qualitative metagenomic descriptions of holobiont communities associated with honey bees by providing a curated set of barcode sequences. The goal of genetic barcoding is to associate a nucleotide sequence sample to a taxonomically valid species. Genomic regions targeted for such barcoding purposes varied by taxonomic group. The small subunit (SSU) ribosomal RNA, or 16S rRNA, is the most commonly used barcode for bacteria and is used in HB-Barcode. These 16S rRNA sequences will support the analysis of data generated with the widely used approach of amplicon-based 16S rRNA deep sequencing to study microbiota communities. Although barcode markers for fungi are less definitive than bacteria, HB-Barcode defaults to the ribosomal RNA internal transcribed spacer region (ITS), which typically includes ITS-1, 5.8S, and ITS-2. For some clades that cannot be resolved by this region, other barcode markers were selected. The majority of barcodes for metazoan taxa are the mitochondrial locus cytochrome c oxidase subunit I (COI). Complete mitochondrial DNA (mtDNA) sequence for Apis cerana (Asian honey bee) and Galleria mellonella (Greater wax moth) are included as barcodes for these species. We note that A. cerana mtDNA is included because it is considered a potentially invasive honey bee species and monitoring for its occurrence is in practice regionally, including in Australia, New Zealand and the USA. Protozoan barcodes include cytochrome b oxidase (Cytb), SSU, or ITS while entire genomes are used for viral barcoding. HoloBee-Mop is a database comprised mostly of chromosomal, mitochondrial and plasmid genome assemblies in order to aggregate as much honey bee holobiont genomic sequence information as possible. For a few organisms without genome assembly data, transcriptome data are included (e.g. Aethina tumida, small hive beetle). Unlike HoloBee-Barcode, redundancy removal was not performed on the HoloBee-Mop database and thus this resource provides an archive of nucleotide sequence assemblies from honey bee holobionts. However, since full viral genomes are used in HoloBee-Barcode, only redundant viral sequences occur in HoloBee-Mop. All accessions within each of these assemblies were concatenated into a single fasta formatted file to create the HoloBee-Mop database. The intended purpose of HoloBee-Mop is to improve honey bee genome and transcriptome assemblies by “mopping-up” as much viral, bacterial, fungal, protozoan and non-honey bee metazoan sequence data as possible. Therefore, sequence data remaining after processing reads through both HoloBee-Barcode and HoloBee-Mop that do not map to the honey bee genome may contain unique data from taxonomic variants or novel species. Details for each sequence assembly within HoloBee-Mop are tabulated in cross reference tables according to each major taxonomic group. HoloBee-Mop assembly counts are: Viruses = 2; Bacteria = 55; Fungi = 5; Protozoa = 1; Metazoa = 6. Follow the HoloBee database on Twitter at: https://twitter.com/HoloBee_db For questions about the HoloBee database, contact: HoloBee database team: holobee.db@gmail.com Jay Evans: Jay.Evans@ars.usda.gov Anna Childers: Anna.Childers@ars.usda.gov

Manitowoc R UVDOC data 2011. This dataset is associated with the following publication: Williamson, C., S. Madronich, A. Lal, R. Zepp, R. Lucas, E. Overholt, K. Rose, S.G. Schladow, and J. Lee-Taylor. Altmetric: 165More detail Article | OPEN Climate change-induced increases in precipitation are reducing the potential for solar ultraviolet radiation to inactivate pathogens in surface waters. Scientific Reports. Nature Publishing Group, London, UK, 7: 13033, (2017).