Genome Sequence of “Candidatus Mycoplasma haemolamae” Strain Purdue,a Red Blood Cell Pathogen of Alpacas (Vicugna pacos) and Llamas (Lama glama)

We report the complete genome sequence of “Candidatus Mycoplasma haemolamae,” an endemic red-cell pathogen of camelids. The single, circular chromosome has 756,845 bp, a 39.3% G+C content, and 925 coding sequences (CDSs). A great proportion (49.1%) of these CDSs are organized into paralogous gene families, which can now be further explored with regard to antigenic variation.     

Physiological responses after two different CrossFit workouts

The present study aimed to investigate the physiological response to CrossFit “workouts of the day” (WODs) based on two different structures of training session: 1) the “as many repetitions as possible” (AMRAP) “Cindy” and 2) the “round for time” (RFT) “Open 18.4” session. CrossFit athletes (11 men and 12 women) were divided into two groups: 1) one performing the WOD “Cindy” (GC) and 2) one performing the WOD “Open 18.4” (GO). Before, immediately after and 30 min after WODs, blood lactate (LAC), heart rate (HR) and systolic and diastolic blood pressures (SBP and DBP) were measured. A two-way ANOVA indicated differences in physiological responses between GC and GO. Both WODs increased HR to similar levels. Only GO significantly increased SBP immediately after exercise compared to the rest period (p < 0.01), with no difference to GC. GO presented higher levels of LAC immediately after exercise compared to GC (15.8 ± 4.9 mM [GO] vs 9.3 ± 2.3 mM [GC]; p < 0.01). LAC remained different between the groups 30 min after exercise (7.0 ± 3.9 mM [GO] vs 3.9 ± 0.9 mM [GC]; p < 0.01). The results suggest that the studied WODs do not differ in acute cardiovascular responses, but depend on different metabolic demands, with RFT structure relying more on glycolytic metabolism (indicated by greater LAC levels after exercise in GO). Such results are in agreement independent of gender.     

Analysis of Pharmacogenomic Variants Associated with Population Differentiation

In the present study, we systematically investigated population differentiation of drug-related (DR) genes in order to identify common genetic features underlying population-specific responses to drugs. To do so, we used the International HapMap project release 27 Data and Pharmacogenomics Knowledge Base (PharmGKB) database. First, we compared four measures for assessing population differentiation: the chi-square test, the analysis of variance (ANOVA) F-test, F_st, and Nearest Shrunken Centroid Method (NSCM). F_st showed high sensitivity with stable specificity among varying sample sizes; thus, we selected F_st for determining population differentiation. Second, we divided DR genes from PharmGKB into two groups based on the degree of population differentiation as assessed by F_st: genes with a high level of differentiation (HD gene group) and genes with a low level of differentiation (LD gene group). Last, we conducted a gene ontology (GO) analysis and pathway analysis. Using all genes in the human genome as the background, the GO analysis and pathway analysis of the HD genes identified terms related to cell communication. “Cell communication” and “cell-cell signaling” had the lowest Benjamini-Hochberg’s q-values (0.0002 and 0.0006, respectively), and “drug binding” was highly enriched (16.51) despite its relatively high q-value (0.0142). Among the 17 genes related to cell communication identified in the HD gene group, five genes (STX4, PPARD, DCK, GRIK4, and DRD3) contained single nucleotide polymorphisms with F_st values greater than 0.5. Specifically, the F_st values for rs10871454, rs6922548, rs3775289, rs1954787, and rs167771 were 0.682, 0.620, 0.573, 0.531, and 0.510, respectively. In the analysis using DR genes as the background, the HD gene group contained six significant terms. Five were related to reproduction, and one was “Wnt signaling pathway,” which has been implicated in cancer. Our analysis suggests that the HD gene group from PharmGKB is associated with cell communication and drug binding.     

“Candidatus Accumulibacter” Population Structure in Enhanced Biological Phosphorus Removal Sludges as Revealed by Polyphosphate Kinase Genes

We investigated the fine-scale population structure of the “Candidatus Accumulibacter” lineage in enhanced biological phosphorus removal (EBPR) systems using the polyphosphate kinase 1 gene (ppk1) as a genetic marker. We retrieved fragments of “Candidatus Accumulibacter” 16S rRNA and ppk1 genes from one laboratory-scale and several full-scale EBPR systems. Phylogenies reconstructed using 16S rRNA genes and ppk1 were largely congruent, with ppk1 granting higher phylogenetic resolution and clearer tree topology and thus serving as a better genetic marker than 16S rRNA for revealing population structure within the “Candidatus Accumulibacter” lineage. Sequences from at least five clades of “Candidatus Accumulibacter” were recovered by ppk1-targeted PCR, and subsequently, specific primer sets were designed to target the ppk1 gene for each clade. Quantitative real-time PCR (qPCR) assays using “Candidatus Accumulibacter”-specific 16S rRNA and “Candidatus Accumulibacter” clade-specific ppk1 primers were developed and conducted on three laboratory-scale and nine full-scale EBPR samples and two full-scale non-EBPR samples to determine the abundance of the total “Candidatus Accumulibacter” lineage and the relative distributions and abundances of the five “Candidatus Accumulibacter” clades. The qPCR-based estimation of the total “Candidatus Accumulibacter” fraction as a proportion of the bacterial community as measured using 16S rRNA genes was not significantly different from the estimation measured using ppk1, demonstrating the power of ppk1 as a genetic marker for detection of all currently defined “Candidatus Accumulibacter” clades. The relative distributions of “Candidatus Accumulibacter” clades varied among different EBPR systems and also temporally within a system. Our results suggest that the “Candidatus Accumulibacter” lineage is more diverse than previously realized and that different clades within the lineage are ecologically distinct.     

Chapter 9: Analyses Using Disease Ontologies

Advanced statistical methods used to analyze high-throughput data such as gene-expression assays result in long lists of “significant genes.” One way to gain insight into the significance of altered expression levels is to determine whether Gene Ontology (GO) terms associated with a particular biological process, molecular function, or cellular component are over- or under-represented in the set of genes deemed significant. This process, referred to as enrichment analysis, profiles a gene-set, and is widely used to makes sense of the results of high-throughput experiments. The canonical example of enrichment analysis is when the output dataset is a list of genes differentially expressed in some condition. To determine the biological relevance of a lengthy gene list, the usual solution is to perform enrichment analysis with the GO. We can aggregate the annotating GO concepts for each gene in this list, and arrive at a profile of the biological processes or mechanisms affected by the condition under study. While GO has been the principal target for enrichment analysis, the methods of enrichment analysis are generalizable. We can conduct the same sort of profiling along other ontologies of interest. Just as scientists can ask “Which biological process is over-represented in my set of interesting genes or proteins?” we can also ask “Which disease (or class of diseases) is over-represented in my set of interesting genes or proteins?“. For example, by annotating known protein mutations with disease terms from the ontologies in BioPortal, Mort et al. recently identified a class of diseases—blood coagulation disorders—that were associated with a 14-fold depletion in substitutions at O-linked glycosylation sites. With the availability of tools for automatic annotation of datasets with terms from disease ontologies, there is no reason to restrict enrichment analyses to the GO. In this chapter, we will discuss methods to perform enrichment analysis using any ontology available in the biomedical domain. We will review the general methodology of enrichment analysis, the associated challenges, and discuss the novel translational analyses enabled by the existence of public, national computational infrastructure and by the use of disease ontologies in such analyses.

What to Learn in This Chapter

• Review the commonly used approach of Gene Ontology based enrichment analysis
• Understand the pitfalls associated with current approaches
• Understand the national infrastructure available for using alternative ontologies for enrichment analysis
• Learn about a generalized enrichment analysis workflow and its application using disease ontologies

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

Aspects of Embryonic and Larval Development in Bighead Carp Hypophthalmichthys nobilis and Silver Carp Hypophthalmichthys molitrix

As bighead carp Hypophthalmichthys nobilis and silver carp H . molitrix (the bigheaded carps) are poised to enter the Laurentian Great Lakes and potentially damage the region’s economically important fishery, information on developmental rates and behaviors of carps is critical to assessing their ability to establish sustainable populations within the Great Lakes basin. In laboratory experiments, the embryonic and larval developmental rates, size, and behaviors of bigheaded carp were tracked at two temperature treatments, one “cold” and one “warm”. Developmental rates were computed using previously described stages of development and the cumulative thermal unit method. Both species have similar thermal requirements, with a minimum developmental temperature for embryonic stages of 12.1° C for silver carp and 12.9° C for bighead carp, and 13.3° C for silver carp larval stages and 13.4° C for bighead carp larval stages. Egg size differed among species and temperature treatments, as egg size was larger in bighead carp, and “warm" temperature treatments. The larvae started robust upwards vertical swimming immediately after hatching, interspersed with intervals of sinking. Vertical swimming tubes were used to measure water column distribution, and ascent and descent rates of vertically swimming fish. Water column distribution and ascent and descent rates changed with ontogeny. Water column distribution also showed some diel periodicity. Developmental rates, size, and behaviors contribute to the drift distance needed to fulfill the early life history requirements of bigheaded carps and can be used in conjunction with transport information to assess invasibility of a river.