BackgroundMass transit environments, such as subways, are uniquely important for transmission of microbes among humans and built environments, and for their ability to spread pathogens and impact large numbers of people. In order to gain a deeper understanding of microbiome dynamics in subways, we must identify variables that affect microbial composition and those microorganisms that are unique to specific habitats.MethodsWe performed high-throughput 16S rRNA gene sequencing of air and surface samples from 16 subway stations in Oslo, Norway, across all four seasons. Distinguishing features across seasons and between air and surface were identified using random forest classification analyses, followed by in-depth diversity analyses.ResultsThere were significant differences between the air and surface bacterial communities, and across seasons. Highly abundant groups were generally ubiquitous; however, a large number of taxa with low prevalence and abundance were exclusively present in only one sample matrix or one season. Among the highly abundant families and genera, we found that some were uniquely so in air samples. In surface samples, all highly abundant groups were also well represented in air samples. This is congruent with a pattern observed for the entire dataset, namely that air samples had significantly higher within-sample diversity. We also observed a seasonal pattern: diversity was higher during spring and summer. Temperature had a strong effect on diversity in air but not on surface diversity. Among-sample diversity was also significantly associated with air/surface, season, and temperature.ConclusionsThe results presented here provide the first direct comparison of air and surface bacterial microbiomes, and the first assessment of seasonal variation in subways using culture-independent methods. While there were strong similarities between air and surface and across seasons, we found both diversity and the abundances of certain taxa to differ. This constitutes a significant step towards understanding the composition and dynamics of bacterial communities in subways, a highly important environment in our increasingly urbanized and interconnect world.
The 3’,5’-cyclic adenosine monophosphate (cAMP)-dependent protein kinase, or protein kinase A (PKA), pathway is one of the most versatile and best studied signaling pathways in eukaryotic cells. The two paralogous PKA catalytic subunits Cα and Cβ, encoded by the genes PRKACA and PRKACB, respectively, are among the best understood model kinases in signal transduction research. In this work, we explore and elucidate the evolution of the alternative 5’ exons and the splicing pattern giving rise to the numerous PKA catalytic subunit isoforms. In addition to the universally conserved Cα1/Cβ1 isoforms, we find kinase variants with short N-termini in all main vertebrate classes, including the sperm-specific Cα2 isoform found to be conserved in all mammals. We also describe, for the first time, a PKA Cα isoform with a long N-terminus, paralogous to the PKA Cβ2 N-terminus. An analysis of isoform-specific variation highlights residues and motifs that are likely to be of functional importance.
BackgroundAs an intracellular human pathogen, Mycobacterium tuberculosis (Mtb) is facing multiple stressful stimuli inside the macrophage and the granuloma. Understanding Mtb responses to stress is essential to identify new virulence factors and pathways that play a role in the survival of the tubercle bacillus. The main goal of this study was to map the regulatory networks of differentially expressed (DE) transcripts in Mtb upon various forms of genotoxic stress. We exposed Mtb cells to oxidative (H2O2 or paraquat), nitrosative (DETA/NO), or alkylation (MNNG) stress or mitomycin C, inducing double-strand breaks in the DNA. Total RNA was isolated from treated and untreated cells and subjected to high-throughput deep sequencing. The data generated was analysed to identify DE genes encoding mRNAs, non-coding RNAs (ncRNAs), and the genes potentially targeted by ncRNAs.ResultsThe most significant transcriptomic alteration with more than 700 DE genes was seen under nitrosative stress. In addition to genes that belong to the replication, recombination and repair (3R) group, mainly found under mitomycin C stress, we identified DE genes important for bacterial virulence and survival, such as genes of the type VII secretion system (T7SS) and the proline-glutamic acid/proline-proline-glutamic acid (PE/PPE) family. By predicting the structures of hypothetical proteins (HPs) encoded by DE genes, we found that some of these HPs might be involved in mycobacterial genome maintenance. We also applied a state-of-the-art method to predict potential target genes of the identified ncRNAs and found that some of these could regulate several genes that might be directly involved in the response to genotoxic stress.ConclusionsOur study reflects the complexity of the response of Mtb in handling genotoxic stress. In addition to genes involved in genome maintenance, other potential key players, such as the members of the T7SS and PE/PPE gene family, were identified. This plethora of responses is detected not only at the level of DE genes encoding mRNAs but also at the level of ncRNAs and their potential targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3132-1) contains supplementary material, which is available to authorized users.
Background: Aerosol microbiome research advances our understanding of bioaerosols, including how airborne microorganisms affect our health and surrounding environment. Traditional microbiological/molecular methods are commonly used to study bioaerosols, but do not allow for generic, unbiased microbiome profiling. Recent studies have adopted shotgun metagenomic sequencing (SMS) to address this issue. However, SMS requires relatively large DNA inputs, which are challenging when studying low biomass air environments, and puts high requirements on air sampling, sample processing and DNA isolation protocols. Previous SMS studies have consequently adopted various mitigation strategies, including long-duration sampling, sample pooling, and whole genome amplification, each associated with some inherent drawbacks/limitations. Results: Here, we demonstrate a new custom, multi-component DNA isolation method optimized for SMS-based aerosol microbiome research. The method achieves improved DNA yields from filter-collected air samples by isolating DNA from the entire filter extract, and ensures a more comprehensive microbiome representation by combining chemical, enzymatic and mechanical lysis. Benchmarking against two state-of-the-art DNA isolation methods was performed with a mock microbial community and real-world air samples. All methods demonstrated similar performance regarding DNA yield and community representation with the mock community. However, with subway samples, the new method obtained drastically improved DNA yields, while SMS revealed that the new method reported higher diversity. The new method involves intermediate filter extract separation into a pellet and supernatant fraction. Using subway samples, we demonstrate that supernatant inclusion results in improved DNA yields. Furthermore, SMS of pellet and supernatant fractions revealed overall similar taxonomic composition but also identified differences that could bias the microbiome profile, emphasizing the importance of processing the entire filter extract. Conclusions: By demonstrating and benchmarking a new DNA isolation method optimized for SMS-based aerosol microbiome research with both a mock microbial community and real-world air samples, this study contributes to improved selection, harmonization, and standardization of DNA isolation methods. Our findings highlight the importance of ensuring end-to-end sample integrity and using methods with well-defined performance characteristics. Taken together, the demonstrated performance characteristics suggest the new method could be used to improve the quality of SMS-based aerosol microbiome research in low biomass air environments.
Protein kinase A (PKA) is a holoenzyme composed of a regulatory subunit dimer and two catalytic subunits and regulates numerous cellular functions including immune cell activity. There are two major catalytic subunit genes, PRKACA and PRKACB encoding the catalytic subunits Cα and Cβ. The PRKACB gene encodes several splice variants including Cβ2, which is enriched in T-, B- and natural killer cells. Cβ2 is significantly larger (46 kDa) than any other C splice variant. In this study we characterized mice ablated for the Cβ2 protein demonstrating a significantly reduced cAMP-induced catalytic activity of PKA in the spleenocytes, lymphocytes and thymocytes. We also observed a significantly increased number of CD62L-expressing CD4 and CD8 T cells in LNs, accompanied by increased susceptibility to systemic inflammation by the Cβ2 ablated mice. The latter was reflected in an elevated sensitivity to collagen-induced arthritis (CIA), as well as higher concentration of TNF-α and lower concentration of IL-10 in response to LPS challenges. We suggest a role of Cβ2 in regulating innate as well as adaptive immune sensitivity in vivo.
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