Patchiness of phytoplankton and primary production in Liaodong Bay, China

<div><p>A comprehensive study of water quality, phytoplankton biomass, and photosynthetic rates in Liaodong Bay, China, during June and July of 2013 revealed two large patches of high biomass and production with dimensions on the order of 10 km. Nutrient concentrations were above growth-rate-saturating concentrations throughout the bay, with the possible exception of phosphate at some stations. The presence of the patches therefore appeared to reflect the distribution of water temperature and variation of light penetration restricted by water turbidity. There was no patch of high phytoplankton biomass or production in a third, linear patch of water with characteristics suitable for rapid phytoplankton growth; the absence of a bloom in that patch likely reflected the fact that the width of the patch was less than the critical size required to overcome losses of phytoplankton to turbulent diffusion. The bottom waters of virtually all of the eastern half of the bay were below the depth of the mixed layer, and the lowest bottom water oxygen concentrations, 3–5 mg L^–1, were found in that part of the bay. The water column in much of the remainder of the bay was within the mixed layer, and oxygen concentrations in both surface and bottom waters exceeded 5 mg L^–1.</p></div

Contour maps of photosynthetic rates (Panel A, in mg C m^–3 h^–1), concentrations of Chl <i>a</i> (Panel B, in mg m^–3) and assimilation numbers (Panel C, in mg C mg^–1 Chl <i>a</i> h^–1), dissolved inorganic nitrogen (DIN, Panel D, in μM), silicate (SiO₃-Si, Panel E, in μM), and phosphate (PO₄-P, Panel F, in μM).

<p>Triangles in F denote stations with phosphate concentrations less than 25 nM.</p

Study area, sampling stations (● and △) and ¹⁴C incubation stations (△) in Liaodong Bay, China.

<p>Study area, sampling stations (● and △) and ¹⁴C incubation stations (△) in Liaodong Bay, China.</p

Contour maps and/or corresponding location maps of temperature (Panels A and B, in °C), Secchi-disk depth (Panels C and D, in meters), Secchi-disk depth associated with temperature (Panel E), and dissolved oxygen (DO, Panel F, in mg L^–1).

<p>Contour maps and/or corresponding location maps of temperature (Panels A and B, in °C), Secchi-disk depth (Panels C and D, in meters), Secchi-disk depth associated with temperature (Panel E), and dissolved oxygen (DO, Panel F, in mg L^–1).</p

Relationship between DO concentrations and salinity (Panel A) and location of stations in three groups with different DO concentrations (Panel B).

<p>In Panels A and B, circle dots denote stations with high DO of more than 13 mg L^–1 at a salinity of 1 to low DO concentrations of 3–5 mg L^–1 at salinities of 16–26; Triangles and plus signs denote stations with DO concentrations of roughly 7–9 mg L^–1 and 9–11 mg L^–1, respectively, in both cases at salinities of 20–28.</p

A Refined View of Airway Microbiome in Chronic Obstructive Pulmonary Disease at Species and Strain-Levels

Wang, Liu, Wang, Yang, Wang, Chen, Stampfli, Zhou, Shu, Brightling, Liang and Chen. Little is known about the underlying airway microbiome diversity in chronic obstructive pulmonary disease (COPD) at in-depth taxonomic levels. Here we present the first insights on the COPD airway microbiome at species and strain-levels. The full-length 16S rRNA gene was characterized from sputum in 98 COPD patients and 27 age-matched healthy controls, using the Pacific Biosciences sequencing platform. Individual species within the same genus exhibited reciprocal relationships with COPD and disease severity. Species dominant in health can be taken over by another species within the same genus but with potentially increasing pathogenicity in severe COPD patients. Ralstonia mannitolilytica, an opportunistic pathogen, was significantly increased in frequent exacerbators (fold-change = 4.94, FDR P = 0.005). There were distinct patterns of interaction between bacterial species and host inflammatory mediators according to neutrophilic or eosinophilic inflammations, two major airway inflammatory phenotypes in COPD. Haemophilus influenzae, Moraxella catarrhalis, Pseudomonas aeruginosa, and Neisseria meningitidis were associated with enhanced Th1, Th17 and pro-inflammatory mediators, while a group of seven species including Tropheryma whipplei were specifically associated with Th2 mediators related to eosinophilia. We developed an automated pipeline to assign strain-level taxonomy leveraging bacterial intra-genomic 16S allele frequency. Using this pipeline we further resolved three non-typeable H. influenzae strains PittEE, PittGG and 86-028NP with reasonable precision and uncovered strain-level variation related to airway inflammation. In particular, 86-028NP and PittGG strains exhibited inverse associations with Th2 chemokines CCL17 and CCL13, suggesting their abundances may inversely predict eosinophilic inflammation. A systematic comparison of 16S hypervariable regions indicated V1V3 instead of the commonly used V4 region was the best surrogate for airway microbiome. The full-length 16S data augmented the power of functional inference, which slightly better recapitulated the actual metagenomes. This led to the unique identification of butyrate-producing and nitrate reduction pathways as depleted in COPD. Our analysis uncovered finer-scale airway microbial diversity that was previously underappreciated, thus enabled a refined view of the airway microbiome in COPD