Phylogenetically and metabolically diverse autotrophs in the world's deepest blue hole

The world's deepest yongle blue hole (YBH) is characterized by sharp dissolved oxygen (DO) gradients, and considerably low-organic-carbon and high-inorganic-carbon concentrations that may support active autotrophic communities. To understand metabolic strategies of autotrophic communities for obtaining carbon and energy spanning redox gradients, we presented finer characterizations of microbial community, metagenome and metagenome-assembled genomes (MAGs) in the YBH possessing oxic, hypoxic, essentially anoxic and completely anoxic zones vertically. Firstly, the YBH microbial composition and function shifted across the four zones, linking to different biogeochemical processes. The recovery of high-quality MAGs belonging to various uncultivated lineages reflected high novelty of the YBH microbiome. Secondly, carbon fixation processes and associated energy metabolisms varied with the vertical zones. The Calvin-Benson-Bassham (CBB) cycle was ubiquitous but differed in affiliated taxa at different zones. Various carbon fixation pathways were found in the hypoxic and essentially anoxic zones, including the 3-hyroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle affiliated to Nitrososphaeria, and Wood-Ljungdahl (WL) pathway affiliated to Planctomycetes, with sulfur oxidation and dissimilatory nitrate reduction as primary energy-conserving pathways. The completely anoxic zone harbored diverse taxa (Dehalococcoidales, Desulfobacterales and Desulfatiglandales) utilizing the WL pathway coupled with versatile energy-conserving pathways via sulfate reduction, fermentation, CO oxidation and hydrogen metabolism. Finally, most of the WL-pathway containing taxa displayed a mixotrophic lifestyle corresponding to flexible carbon acquisition strategies. Our result showed a vertical transition of microbial lifestyle from photo-autotrophy, chemoautotrophy to mixotrophy in the YBH, enabling a better understanding of carbon fixation processes and associated biogeochemical impacts with different oxygen availability.

Photobacterium obscurum sp. nov., a marine bacterium isolated from the coast of Qingdao

A Gram-stain-negative, facultative anaerobic, rod-shaped strain, named SDRW27T, was isolated from offshore seawater collected near Qingdao. Strain SDRW27T was able to grow at 16-37 °C (optimum, 28 °C), pH 6.0-9.0 (optimum, pH 6.0) and in the presence of 1-7 % (w/v) NaCl (optimum, 3 %). Phylogenetic analysis using 16S rRNA gene sequences indicated that strain SDRW27T was most closely related to Photobacterium toruni H01100410BT (97.89 % sequence similarity), Photobacterium andalusiense H01100409BT (97.89 %) and Photobacterium leiognathi ATCC 25521T (97.82 %). The predominant fatty acids were summed feature 3 (C16 : 1 ω7c and/or iso-C15 : 0 2-OH), summed feature 8 (C18 : 1  ω7c and/or C18 : 1  ω6c) and C16 : 0. The polar lipids of strain SDRW27T comprised phosphatidylglycerol, phosphatidylinositol dimannoside, phosphatidylcholine, phosphatidylethanolamine and three unidentified lipids. The major respiratory quinone was ubiquinone-8. The G+C content was 47.71 mol%. The genome size was 5.84 Mbp, including 85 contigs with an N50 value of 223 542. The average nucleotide identity (ANI) values of SDRW27T with its three most similar strains, P. toruni H01100410BT, P. andalusiense H01100409BT and P. leiognathi ATCC 25521T, were 71.36, 71.58 and 72.23 %, respectively (all lower than the 95-96 % ANI threshold), and the DNA-DNA hybridization (DDH) values were 20.4, 20.8 and 20.4 % (all lower than the 70 % DDH threshold). The obtained results of polyphasic analysis demonstrate that strain SDRW27T represents a novel species, for which the name Photobacterium obscurum sp. nov. is proposed. The type strain is SDRW27T (=MCCC 1K06286T=KCTC 82892T).

An IncN-ST7 epidemic plasmid mediates the dissemination of carbapenem-resistant Klebsiella pneumoniae in a neonatal intensive care unit in China over 10 years

OBJECTIVES

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has widely disseminated globally, but its epidemiological characterization and clinical significance in paediatric patients are not well understood. In this study, we aimed to trace the dissemination dynamics of CRKP in the neonatal intensive care unit (NICU) of a tertiary hospital over a 10-y period.

METHODS

We collected 67 non-duplicate K. pneumoniae species complex isolates from the NICU with patient metadata during 2009-2018. Antimicrobial susceptibility was determined by the agar or broth microdilution method. Risk factors for CRKP-positive patients were identified by univariate and multivariate analysis. Genetic characterization was dissected by whole-genome sequencing. Plasmid transmissibility, stability, and fitness were assessed.

RESULTS

Thirty-four of 67 isolates (50.75%) were identified as CRKP. Premature rupture of membranes, gestational age, and invasive procedures are independent risk factors for CRKP-positive patients. The annual isolation rate of CRKP varied between 0% and 88.9%, and multiple clonal replacements were observed during the study period, which could be largely due to the division of the NICU. All but one CRKP produced IMP-4 carbapenemase, which was encoded by an IncN-ST7 epidemic plasmid, suggesting that the IncN-ST7 plasmid mediated the CRKP dissemination in the NICU over 10 y. The same plasmid was found in several CRKP isolates from adult patients, of which two ST17 isolates from the neurosurgery department shared a high homology with the ST17 isolates from the NICU, indicating possible cross-departmental transmission.

CONCLUSION

Our study highlights the urgent need for infection control measures targeting high-risk plasmids like IncN-ST7.

Microbial communities related to the sulfur cycle in the Sansha Yongle Blue Hole

The Sansha Yongle Blue Hole (SYBH), the deepest blue hole in the world, is an excellent habitat for revealing biogeochemical cycles in the anaerobic environment. However, how sulfur cycling is mediated by microorganisms in the SYBH hasn't been fully understood. In this study, the water layers of the SYBH were divided into oxic zone, hypoxic zone, anoxic zone I and II, and microbial-mediated sulfur cycling in the SYBH was comprehensively interpreted. The 16S rRNA genes/transcripts analyses showed that the microbial community structures associated with the sulfur cycling in each zone had distinctive features. Sulfur-oxidizing bacteria were mostly constituted by Gammaproteobacteria, Alphaproteobacteria, Campylobacterota, and Chlorobia above the anoxic zone I and sulfate-reducing bacteria were dominated by Desulfobacterota in anoxic zones. Metagenomic analyses showed that the sulfide-oxidation-related gene sqr and genes encoding the Sox system were mainly distributed in the anoxic zone I, while genes related to dissimilatory sulfate reduction and sulfur intermediate metabolite reduction were mainly distributed in the anoxic zone II, indicating different sulfur metabolic processes between these two zones. Moreover, sulfur-metabolism-related genes were identified in 81 metagenome-assembled genomes (MAGs), indicating a high diversity of microbial communities involved in sulfur cycling. Among them, three MAGs from the candidate phyla JdFR-76 and AABM5-125-24 with genes related to dissimilatory sulfate reduction exhibited distinctive metabolic features. Our results showed unique and novel microbial populations in the SYBH sulfur cycle correlated to the sharp redox gradients, revealing complex biogeochemical processes in this extreme environment. IMPORTANCE Oxygen-deficient regions in the global ocean are expanding rapidly and affect the growth, reproduction and ecological processes of marine organisms. The anaerobic water body of about 150 m in the Sansha Yongle Blue Hole (SYBH) provided a suitable environment to study the specific microbial metabolism in anaerobic seawater. Here, we found that the vertical distributions of the total and active communities of sulfur-oxidizing bacteria (SOB) and sulfate-reducing bacteria (SRB) were different in each water layer of the SYBH according to the dissolved oxygen content. Genes related to sulfur metabolism also showed distinct stratification characteristics. Furthermore, we have obtained diverse metagenome-assembled genomes, some of which exhibit special sulfur metabolic characteristics, especially candidate phyla JdFR-76 and AABM5-125-24 were identified as potential novel SRB. The results of this study will promote further understanding of the sulfur cycle in extreme environments, as well as the environmental adaptability of microorganisms in blue holes.

Deep-sea Bacteroidetes from the Mariana Trench specialize in hemicellulose and pectin degradation typically associated with terrestrial systems

BACKGROUND

Hadal trenches (>6000 m) are the deepest oceanic regions on Earth and depocenters for organic materials. However, how these enigmatic microbial ecosystems are fueled is largely unknown, particularly the proportional importance of complex polysaccharides introduced through deposition from the photic surface waters above. In surface waters, Bacteroidetes are keystone taxa for the cycling of various algal-derived polysaccharides and the flux of carbon through the photic zone. However, their role in the hadal microbial loop is almost unknown.

RESULTS

Here, culture-dependent and culture-independent methods were used to study the potential of Bacteroidetes to catabolize diverse polysaccharides in Mariana Trench waters. Compared to surface waters, the bathypelagic (1000-4000 m) and hadal (6000-10,500 m) waters harbored distinct Bacteroidetes communities, with Mesoflavibacter being enriched at ≥ 4000 m and Bacteroides and Provotella being enriched at 10,400-10,500 m. Moreover, these deep-sea communities possessed distinct gene pools encoding for carbohydrate active enzymes (CAZymes), suggesting different polysaccharide sources are utilised in these two zones. Compared to surface counterparts, deep-sea Bacteroidetes showed significant enrichment of CAZyme genes frequently organized into polysaccharide utilization loci (PULs) targeting algal/plant cell wall polysaccharides (i.e., hemicellulose and pectin), that were previously considered an ecological trait associated with terrestrial Bacteroidetes only. Using a hadal Mesoflavibacter isolate (MTRN7), functional validation of this unique genetic potential was demonstrated. MTRN7 could utilize pectic arabinans, typically associated with land plants and phototrophic algae, as the carbon source under simulated deep-sea conditions. Interestingly, a PUL we demonstrate is likely horizontally acquired from coastal/land Bacteroidetes was activated during growth on arabinan and experimentally shown to encode enzymes that hydrolyze arabinan at depth.

CONCLUSIONS

Our study implies that hadal Bacteroidetes exploit polysaccharides poorly utilized by surface populations via an expanded CAZyme gene pool. We propose that sinking cell wall debris produced in the photic zone can serve as an important carbon source for hadal heterotrophs and play a role in shaping their communities and metabolism. Video Abstract.

A point mutation in recC associated with subclonal replacement of carbapenem-resistant Klebsiella pneumoniae ST11 in China

Adaptation to selective pressures is crucial for clinically important pathogens to establish epidemics, but the underlying evolutionary drivers remain poorly understood. The current epidemic of carbapenem-resistant Klebsiella pneumoniae (CRKP) poses a significant threat to public health. In this study we analyzed the genome sequences of 794 CRKP bloodstream isolates collected in 40 hospitals in China between 2014 and 2019. We uncovered a subclonal replacement in the predominant clone ST11, where the previously prevalent subclone OL101:KL47 was replaced by O2v1:KL64 over time in a stepwise manner. O2v1:KL64 carried a higher load of mobile genetic elements, and a point mutation exclusively detected in the recC of O2v1:KL64 significantly promotes recombination proficiency. The epidemic success of O2v1:KL64 was further associated with a hypervirulent sublineage with enhanced resistance to phagocytosis, sulfamethoxazole-trimethoprim, and tetracycline. The phenotypic alterations were linked to the overrepresentation of hypervirulence determinants and antibiotic genes conferred by the acquisition of an rmpA-positive pLVPK-like virulence plasmid and an IncFII-type multidrug-resistant plasmid, respectively. The dissemination of the sublineage was further promoted by more frequent inter-hospital transmission. The results collectively demonstrate that the expansion of O2v1:KL64 is correlated to a repertoire of genomic alterations convergent in a subpopulation with evolutionary advantages.

Oceanospirillales containing the DMSP lyase DddD are key utilisers of carbon from DMSP in coastal seawater

BACKGROUND

Ubiquitous and diverse marine microorganisms utilise the abundant organosulfur molecule dimethylsulfoniopropionate (DMSP), the main precursor of the climate-active gas dimethylsulfide (DMS), as a source of carbon, sulfur and/or signalling molecules. However, it is currently difficult to discern which microbes actively catabolise DMSP in the environment, why they do so and the pathways used.

RESULTS

Here, a novel DNA-stable isotope probing (SIP) approach, where only the propionate and not the DMS moiety of DMSP was ¹³C-labelled, was strategically applied to identify key microorganisms actively using DMSP and also likely DMS as a carbon source, and their catabolic enzymes, in North Sea water. Metagenomic analysis of natural seawater suggested that Rhodobacterales (Roseobacter group) and SAR11 bacteria were the major microorganisms degrading DMSP via demethylation and, to a lesser extent, DddP-driven DMSP lysis pathways. However, neither Rhodobacterales and SAR11 bacteria nor their DMSP catabolic genes were prominently labelled in DNA-SIP experiments, suggesting they use DMSP as a sulfur source and/or in signalling pathways, and not primarily for carbon requirements. Instead, DNA-SIP identified gammaproteobacterial Oceanospirillales, e.g. Amphritea, and their DMSP lyase DddD as the dominant microorganisms/enzymes using DMSP as a carbon source. Supporting this, most gammaproteobacterial (with DddD) but few alphaproteobacterial seawater isolates grew on DMSP as sole carbon source and produced DMS. Furthermore, our DNA-SIP strategy also identified Methylophaga and other Piscirickettsiaceae as key bacteria likely using the DMS, generated from DMSP lysis, as a carbon source.

CONCLUSIONS

This is the first study to use DNA-SIP with ¹³C-labelled DMSP and, in a novel way, it identifies the dominant microbes utilising DMSP and DMS as carbon sources. It highlights that whilst metagenomic analyses of marine environments can predict microorganisms/genes that degrade DMSP and DMS based on their abundance, it cannot disentangle those using these important organosulfur compounds for their carbon requirements. Note, the most abundant DMSP degraders, e.g. Rhodobacterales with DmdA, are not always the key microorganisms using DMSP for carbon and releasing DMS, which in this coastal system were Oceanospirillales containing DddD. Video abstract.

Frequent convergence of mcr-9 and carbapenemase genes in Enterobacter cloacae complex driven by epidemic plasmids and host incompatibility

Convergence of mcr and carbapenemase genes has been sporadically detected in Enterobacter cloacae complex (ECC) with an upward trend. However, the state of the epidemic and underlying mechanism of such convergence has been poorly understood. In this study, the co-occurrence of MCR and carbapenemases was systematically analyzed in 230 clinical ECC isolates collected between 2000 and 2018 together with a global dataset consisting of 3,559 ECC genomes compiled from GenBank. We identified 48 mcr-9/mcr-10-positive isolates (MCR-ECC) (20.9%) in our collection, and a comparable ratio of MCR-ECC (720/3559, 20.2%) was detected in the global dataset. A high prevalence of carbapenemase-producing MCR-ECC (MCR-CREC) was further identified in the MCR-ECC of both datasets (16/48, 33.3%; 388/720, 53.9%), demonstrating a frequent convergence of mcr-9/10 and carbapenemase genes in ECC worldwide. An epidemic IncHI2/2A plasmid with a highly conserved backbone was identified and largely contributed to the dissemination of mcr-9 in ECC worldwide. A highly conserved IncX3-type NDM-1-carrying plasmid and IncN-type IMP-4-carrying plasmid were additionally detected in MCR-CREC isolated in China. Our surveillance data showed that MCR-CREC emerged (in 2013) much later than MCR-ECC (in 2000), indicating that MCR-CREC could be derived from MCR-ECC by additional captures of carbapenemase-encoding plasmids. Tests of plasmid stability and incompatibility showed that the mcr-9/mcr-10-encoding plasmids with the NDM-1-encoding plasmids stably remained in ECC but incompatible in Escherichia coli, suggesting that the convergence was host-dependent. The findings extend our concern on the convergence of resistance to the last resort antibiotics and highlight the necessity of continued surveillance in the future.

Succession of marine bacteria in response to Ulva prolifera-derived dissolved organic matter

Increasing macroalgal blooms as a consequence of climate warming and coastal eutrophication have profound effects on the marine environment. The outbreaks of Ulva prolifera in the Yellow Sea of China occurring every summer since 2007 to present have formed the world's largest green tide. The green tide releases huge amounts of dissolved organic matter (DOM) to the seawater, causing an organic overload. However, how marine bacteria respond to this issue and the potential impact on the marine environment are still unclear. Here, we monitored the highly temporally resolved dynamics of marine bacterial community that occur in response to Ulva prolifera-derived DOM by performing a 168-h microcosm incubation experiment. DOM inputs significantly increased bacterial abundances within 6 h, decreased bacterial diversity and triggered clear community successions during the whole period of incubation. Vibrio of Gammaproteobacteria robustly and rapidly grew over short timescales (6-24 h), with its relative abundance accounting for up to 52.5% of active bacteria. From 24 to 48 h, some genera of Flavobacteriia grew rapidly, which was more conspicuous at a higher DOM concentration than at a lower concentration. The genus Donghicola of Alphaproteobacteria was predominant at later time points (>48 h). This bacterial community succession was accompanied by significant variations in the activity of 12 different extracellular enzymes, resulting in a rapid reduction of dissolved organic carbon by 74.5% within the first 36 h. In summary, our study demonstrates rapid successions of bacterial community and extracellular enzyme activity after DOM inputs, suggesting that the bacterial response to Ulva prolifera-derived organic matter may contribute to environmental restoration and may pose a health threat due to the bloom of potential pathogenic Vibrio.

DiTing: A Pipeline to Infer and Compare Biogeochemical Pathways From Metagenomic and Metatranscriptomic Data

Metagenomics and metatranscriptomics are powerful methods to uncover key micro-organisms and processes driving biogeochemical cycling in natural ecosystems. Databases dedicated to depicting biogeochemical pathways (for example, metabolism of dimethylsulfoniopropionate (DMSP), which is an abundant organosulfur compound) from metagenomic/metatranscriptomic data are rarely seen. Additionally, a recognized normalization model to estimate the relative abundance and environmental importance of pathways from metagenomic and metatranscriptomic data has not been organized to date. These limitations impact the ability to accurately relate key microbial-driven biogeochemical processes to differences in environmental conditions. Thus, an easy-to-use, specialized tool that infers and visually compares the potential for biogeochemical processes, including DMSP cycling, is urgently required. To solve these issues, we developed DiTing, a tool wrapper to infer and compare biogeochemical pathways among a set of given metagenomic or metatranscriptomic reads in one step, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and a manually created DMSP cycling gene database. Accurate and specific formulae for over 100 pathways were developed to calculate their relative abundance. Output reports detail the relative abundance of biogeochemical pathways in both text and graphical format. DiTing was applied to simulated metagenomic data and resulted in consistent genetic features of simulated benchmark genomic data. Subsequently, when applied to natural metagenomic and metatranscriptomic data from hydrothermal vents and the Tara Ocean project, the functional profiles predicted by DiTing were correlated with environmental condition changes. DiTing can now be confidently applied to wider metagenomic and metatranscriptomic datasets, and it is available at https://github.com/xuechunxu/DiTing.

Vibrio agarilyticus sp. nov., an agar-digesting marine bacterium isolated from coastal seawater in Daya Bay (Guangdong, China)

A Gram-strain-negative, facultatively anaerobic, motile, rod-shaped and flagellated marine bacterium, designated SM6^T, was isolated from surface seawater collected in Daya Bay (Guangdong, China). Phylogenetic analysis based on 16S rRNA gene sequences, multilocus sequence analysis, phylogenomic analysis of single-copy gene families and whole genome data showed that strain SM6^T belonged to the genus Vibrio. The closest phylogenetic relatives of SM6^T were Vibrio plantisponsor MSSRF60^T (97.38 % 16S rRNA gene sequence pairwise similarity), Vibrio variabilis R-40492^T (97.27 %), Vibrio aestuarianus ATCC 35048^T (97.21 %) and Vibrio sagamiensis LC2-047^T (97.3 %). Growth of strain SM6^T occurred at 10-45 °C (optimum 30 °C), at pH 6.0-9.0 (optimum 6.0) and in the presence of 0-10 % (w/v) NaCl (optimum 3-8 %). The predominant fatty acids (>10 %) were summed feature 3 (C_{16 : 1} ω7c or/and C_{16 : 1} ω6c), C_{16 : 0} and summed feature 8 (C_{18 : 1} ω7c or/and C_{18 : 1} ω6c). The DNA G+C content of the assembled genomic sequences was 47.37 % for strain SM6^T. Average nucleotide identity values between SM6^T and its reference species were lower than the threshold for species delineation (95-96 %); in silico DNA-DNA hybridization further showed that the strains shared less than 70 % similarity. On the basis of evidence from the present polyphasic study, strain SM6^T is considered to represent a novel species of the genus Vibrio, for which the name Vibrio agarilyticus sp. nov. is proposed. The type strain is SM6^T (=KCTC 82076^T=MCCC 1K04327 ^T).

Shift and Metabolic Potentials of Microbial Eukaryotic Communities Across the Full Depths of the Mariana Trench

Microbial eukaryotes are widespread and play important roles in marine ecosystems. However, their ecological characteristics in the deep sea (>1,000 m), especially hadal trenches, were largely unknown. Here, we investigated the diversity and metabolic potentials of microbial eukaryotes along the whole water column of the Mariana Trench by metagenomics. Our results showed clear depth-related distribution of microbial eukaryotic community and associated metabolic potentials. Surface seawater was dominated by phototrophic/mixotrophic groups (e.g., Dinoflagellata) and genes involved in biosynthesis (photosynthesis and fatty acid biosynthesis), while deep (bathypelagic and/or hadal) seawaters were enriched with heterotrophic groups (e.g., Bicoecea) and genes related to digestion (lysosomal enzymes and V-type ATPase) and carbohydrate metabolism. Co-occurrence analysis revealed high intra-domain connectivity, indicating that microbial eukaryotic composition was more influenced by microbial eukaryotes themselves than bacteria. Increased abundance of genes associated with unsaturated fatty acid biosynthesis likely plays a role in resisting high hydrostatic pressure. Top1 and hupB genes, responsible for the formation and stabilization of DNA structure, were unique and abundant in the hadal zone and thus may be helpful to stabilize DNA structure in the deep sea. Overall, our results provide insights into the distribution and potential adaptability of microbial eukaryotes in the hadal zone.

Flammeovirga agarivorans sp. nov., an agar-digesting marine bacterium isolated from surface seawater

A Gram-stain-negative, aerobic, gliding, reddish-orange-coloured, rod-shaped strain, designated SR4^T, was isolated from surface seawater sampled at Luhuitou fringing reef (South China Sea). Phylogenetic analyses based on the 16S rRNA gene, phylogenomic analysis of single-copy gene families and whole genome data affiliated it to the genus Flammeovirga. It was most closely related to Flammeovirga yaeyamensis NBRC 100898^T (97.99 % 16S rRNA gene similarity). The genome average nucleotide identity and DNA-DNA relatedness values between strain SR4^T and its reference strains were less than 74.2 and 16.3 %, respectively. Growth occurred at 20-35 °C (optimum, 28 °C), pH 6.0-9.0 (optimum, pH 7.0) and in the presence of 1-6 % (w/v) NaCl (optimum, 2-4 %). The dominant fatty acids were C_16 : 0, iso-C_15 : 0 and C_20 : 4  ω6,9,12,15c. The polar lipid profile of strain SR4^T comprised phosphatidylethanolamine, two glycolipids, two aminophospholipids and three unidentified lipids. The major respiratory quinone was MK-7. The DNA G+C content of strain SR4^T was 34.20 mol%. On the basis of the polyphasic evidence, strain SR4^T is proposed as representing a novel species of the genus Flammeovirga, for which the name Flammeovirga agarivorans sp. nov. is proposed. The type strain is SR4^T (=KCTC 82075^T=MCCC 1A17137^T).

Bacteria are important dimethylsulfoniopropionate producers in marine aphotic and high-pressure environments

Dimethylsulfoniopropionate (DMSP) is an important marine osmolyte. Aphotic environments are only recently being considered as potential contributors to global DMSP production. Here, our Mariana Trench study reveals a typical seawater DMSP/dimethylsulfide (DMS) profile, with highest concentrations in the euphotic zone and decreased but consistent levels below. The genetic potential for bacterial DMSP synthesis via the dsyB gene and its transcription is greater in the deep ocean, and is highest in the sediment.s DMSP catabolic potential is present throughout the trench waters, but is less prominent below 8000 m, perhaps indicating a preference to store DMSP in the deep for stress protection. Deep ocean bacterial isolates show enhanced DMSP production under increased hydrostatic pressure. Furthermore, bacterial dsyB mutants are less tolerant of deep ocean pressures than wild-type strains. Thus, we propose a physiological function for DMSP in hydrostatic pressure protection, and that bacteria are key DMSP producers in deep seawater and sediment.

Dimethylsulfoniopropionate (DMSP) is an osmolyte produced by marine microbes that plays an important role in nutrient cycling and atmospheric chemistry. Here the authors go to the Mariana Trench—the deepest point in the ocean—and find bacteria are key DMSP producers, and that DMSP has a role in protection against high pressure.

Insights into the Vertical Stratification of Microbial Ecological Roles across the Deepest Seawater Column on Earth

The Earth's oceans are a huge body of water with physicochemical properties and microbial community profiles that change with depth, which in turn influences their biogeochemical cycling potential. The differences between microbial communities and their functional potential in surface to hadopelagic water samples are only beginning to be explored. Here, we used metagenomics to investigate the microbial communities and their potential to drive biogeochemical cycling in seven different water layers down the vertical profile of the Challenger Deep (0-10,500 m) in the Mariana Trench, the deepest natural point in the Earth's oceans. We recovered 726 metagenome-assembled genomes (MAGs) affiliated to 27 phyla. Overall, biodiversity increased in line with increased depth. In addition, the genome size of MAGs at ≥4000 m layers was slightly larger compared to those at 0-2000 m. As expected, surface waters were the main source of primary production, predominantly from Cyanobacteria. Intriguingly, microbes conducting an unusual form of nitrogen metabolism were identified in the deepest waters (>10,000 m), as demonstrated by an enrichment of genes encoding proteins involved in dissimilatory nitrate to ammonia conversion (DNRA), nitrogen fixation and urea transport. These likely facilitate the survival of ammonia-oxidizing archaea α lineage, which are typically present in environments with a high ammonia concentration. In addition, the microbial potential for oxidative phosphorylation and the glyoxylate shunt was enhanced in >10,000 m waters. This study provides novel insights into how microbial communities and their genetic potential for biogeochemical cycling differs through the Challenger deep water column, and into the unique adaptive lifestyle of microbes in the Earth's deepest seawater.

Marinobacter salinexigens sp. nov., a marine bacterium isolated from hadal seawater of the Mariana Trench

A Gram-stain-negative, strictly aerobic, non-motile and rod-shaped bacterium, designated ZYF650^T, was isolated from the hadal seawater (9600 m) of the Mariana Trench. Results of phylogenetic analysis based on 16S rRNA gene sequences indicated that ZYF650^T formed a lineage within the family Alteromonadaceae that was distinct from the most closely related species Marinobacter mobilis and Marinobacter nitratireducens with 16S rRNA gene sequences similarities of 98.0 and 97.7 %, respectively. Strain ZYF650^T showed average nucleotide identity values of 75.7 % with Marinobacter hydrocarbonoclasticus, 73.3 % with Marinobacter mobilis and 79.3 % with Marinobacter nitratireducens, and DNA-DNAhybridization values of 21.5, 21.3 and 22.0 % with M. hydrocarbonoclasticus, M. mobilis and M. nitratireducens, respectively, which were lower than the threshold for species delineation. Strain ZYF650^T grew with 0-14 % (w/v) NaCl (optimum, 7-8 %) at a temperature range of 10-45 °C (optimum, 28 °C) and pH 6.0-9.5 (optimum, pH 7.0-8.0). The sole respiratory quinone was ubiquinone-9 (Q-9). The polar lipids in ZYF650^T comprised phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, three unidentified polar lipids, two unidentified aminolipids and two phospholipids. The predominant fatty acids (more than 10 % of total fatty acids) were C_18 : 1 ω9c (21.9 %), C_16 : 0 (21.7 %), C_12 : 0 3-OH (14.0 %), C_16 : 1 ω9c (13.2 %) and C_12 : 0 (12.2 %). The DNA G+C content of strain ZYF650^T was 55.6 %. On the basis of polyphasic taxonomic analysis, strain ZY650^T is considered to represent a novel specie of the genus Marinobacter in the family Alteromonadaceae, for which the name Marinobacter salinexigens sp. nov. is proposed. The type strain is ZYF650^T (=JCM 33013^T=MCCC 1K03552^T).

Ancestral niche separation and evolutionary rate differentiation between sister marine flavobacteria lineages

Marine flavobacteria are specialists for polysaccharide degradation. They dominate in habitats enriched with polysaccharides, but are also prevalent in pelagic environments where polysaccharides are less available. These niches are likely occupied by distinct lineages, but evolutionary processes underlying their niche differentiation remain elusive. Here, genomic analyses and physiological assays indicate that the sister flavobacteria lineages Leeuwenhoekiella and Nonlabens likely explore polysaccharide-rich macroalgae and polysaccharide-poor pelagic niches respectively. Phylogenomic analyses inferred that the niche separation likely occurred anciently and coincided with increased sequence evolutionary rate in Nonlabens compared with Leeuwenhoekiella. Further analyses ruled out the known mechanisms likely driving evolutionary rate acceleration, including reduced selection efficiency, decreased generation time and increased mutation rate. In particular, the mutation rates were determined using an unbiased experimental method, which measures the present-day populations and may not reflect ancestral populations. These data collectively lead to a new hypothesis that an ancestral and transient mutation rate increase resulted in evolutionary rate increase in Nonlabens. This hypothesis was supported by inferring that gains and losses of genes involved in SOS response, a mechanism known to drive transiently increased mutation rate, coincided with evolutionary rate acceleration. Our analyses highlight the evolutionary mechanisms underlying niche differentiation of flavobacteria lineages.

Comparative genomic and metabolic analysis of manganese-oxidizing mechanisms in Celeribacter manganoxidans DY25T: Its adaptation to the environment of polymetallic nodules

Manganese (Mn) nodule is one of the ubiquitous polymetallic concretions and mainly consists of Mn - Fe oxi-hydroxide precipitations. A primary oxidation of Mn(II) to MnO₂, in which microorganisms may play important roles, is followed by agglomeration of MnO₂ into nodules. Celeribater manganoxidans DY25^T, belonging to family Rhodobacteraceae, has ability to catalyze the formation of MnO₂ [1]. The concentration of MnO₂ formed by harvested cells reached 7.08 μM after suspended in 10 mM HEPES (pH 7.5). Genomic and physiological characteristics of strain DY25^T provided a better understanding of its Mn-oxidizing mechanism. Fifteen genes (including four multicopper oxidases) may be involved in Mn(II)-oxidation, whereas only three of them can promote this process. Sulfur-oxidizing activity was detected, which may be associated with manganese oxidation. Genes involved in import and export of primary elemental ingredients (C, N, P and S) and metallic elements (e.g. Mn) were discovered, demonstrating its potential roles in the biogeochemical cycle.

Biogenic production of DMSP and its degradation to DMS-their roles in the global sulfur cycle

Dimethyl sulfide (DMS) is the most abundant form of volatile sulfur in Earth's oceans, and is mainly produced by the enzymatic clevage of dimethylsulfoniopropionate (DMSP). DMS and DMSP play important roles in driving the global sulfur cycle and may affect climate. DMSP is proposed to serve as an osmolyte, a grazing deterrent, a signaling molecule, an antioxidant, a cryoprotectant and/or as a sink for excess sulfur. It was long believed that only marine eukaryotes such as phytoplankton produce DMSP. However, we recently discovered that marine heterotrophic bacteria can also produce DMSP, making them a potentially important source of DMSP. At present, one prokaryotic and two eukaryotic DMSP synthesis enzymes have been identified. Marine heterotrophic bacteria are likely the major degraders of DMSP, using two known pathways: demethylation and cleavage. Many phytoplankton and some fungi can also cleave DMSP. So far seven different prokaryotic and one eukaryotic DMSP lyases have been identified. This review describes the global distribution pattern of DMSP and DMS, the known genes for biosynthesis and cleavage of DMSP, and the physiological and ecological functions of these important organosulfur molecules, which will improve understanding of the mechanisms of DMSP and DMS production and their roles in the environment.

Photobacterium chitinilyticum sp. nov., a marine bacterium isolated from seawater at the bottom of the East China Sea

A Gram-stain-negative, facultative aerobic, motile by a polar flagellum, rod-shaped strain, designated BEI247^T, was isolated from seawater at the bottom of the East China Sea. Phylogenetic analysis of the 16S rRNA gene and whole genome data affiliated it with the genus Photobacterium. It was most closely related to Photobacterium alginatilyticum P03D4^T (97.36 % 16S rRNA gene similarity). Multi-locus sequence analysis (MLSA) revealed a distinct lineage with P. alginatilyticum P03D4^T as its closest relative. Strain BEI247^T was found to have lower than 86.0 % similarities to the type strains of its most closely related species in MLSA, less than 82.3 % using genome average nucleotide identities, and less than 25.3 % in DNA-DNA relatedness studies. Growth occurred at 10-37 °C (optimum, 24 °C), pH 5.0-8.0 (pH 7.0) and in the presence of 1-5 % (w/v) NaCl (3 %). The dominant fatty acids were summed feature 3 (C16 : 1ω7c and/or C16 : 1ω6c) and C16 : 0. The polar lipids of strain BEI247^T comprised phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, two phospholipids and one unknown lipid. The major respiratory quinone was ubiquinone-8 (Q-8). The DNA G+C content of strain BEI247^T was 46.45 mol%. On the basis of the polyphasic evidence, strain BEI247^T is proposed as representing a novel species of the genus Photobacterium, for which the name Photobacterium chitinilyticum sp. nov. is proposed. The type strain is BEI247^T (=JCM 32689^T=MCCC 1K03517^T=KCTC 62619^T).

[Clinical characteristics and prognosis of long-term glucocorticoid users with community-acquired pneumonia]

Objective: To explore the clinical features, etiological features and prognostic risk factors of long-term glucocorticoid users with community-acquired pneumonia (CAP). Methods: A retrospective study included 100 long-term glucocorticoid users with CAP (G-CAP group) from 11 hospitals of China between January 2014 and December 2014, while 100 non-immunocompromised patients with community-acquired pneumonia were enrolled as controls (nICH-CAP group). Characteristics including age, gender, underlying diseases, corticosteroids, symptoms, disease severity, imaging manifestations, etiology, respiratory failure, mechanical ventilation, whether the application of vasoactive drugs, antibiotics application, hospital mortality rate between the two groups were compared, and the prognostic factors of G-CAP were investigated using Logistic regression. Results: The peripheral blood lymphocytes[1.06(0.70, 1.68) vs 1.44 (0.87, 1.98)]in G-CAP group was less than nICH-CAP group (P<0.05). CT with pulmonary interstitial change (28.6% vs 9.9%), the proportion of patients with respiratory failure (25.0% vs 7.0%), mechanical ventilation (9.0% vs 2.0%), noninvasive mechanical ventilation (12.0% vs 2.0%), septic shock (9.0% vs 2.0%), and the hospital mortality rate (13.0% vs 3.0%) in G-CAP group were significantly higher than in nICH-CAP group (all P<0.05). Bacterial infection accounted for the highest proportion of infection (61.3%) in G-CAP group, but also virus infection (19.4%) and mixed infection (16.1%). Pseudomonas accounted for the highest proportion (47.4%) in bacterial infection of G-CAP. Logistic regression analysis showed that peripheral blood lymphocytes (OR=0.004, 95% CI: 0.000-0.234; P<0.05) and respiratory failure (OR=17.766, 95% CI: 4.933-131.0; P<0.05) were independent predictors of death in G-CAP group. Conclusions: The proportion of severe pneumonia and the mortality rate of patients with G-CAP are higher than the patients with nICH-CAP. Lymphopenia and respiratory failure are associated with poor outcome of patients with G-CAP.

Support vector machines-based quantitative structure-property relationship for the prediction of heat capacity

The support vector machine (SVM), as a novel type of learning machine, for the first time, was used to develop a Quantitative Structure-Property Relationship (QSPR) model of the heat capacity of a diverse set of 182 compounds based on the molecular descriptors calculated from the structure alone. Multiple linear regression (MLR) and radial basis function networks (RBFNNs) were also utilized to construct quantitative linear and nonlinear models to compare with the results obtained by SVM. The root-mean-square (rms) errors in heat capacity predictions for the whole data set given by MLR, RBFNNs, and SVM were 4.648, 4.337, and 2.931 heat capacity units, respectively. The prediction results are in good agreement with the experimental value of heat capacity; also, the results reveal the superiority of the SVM over MLR and RBFNNs models.

Diagnosing anorexia based on partial least squares, back propagation neural network, and support vector machines

Support vector machine (SVM), as a novel type of learning machine, for the first time, was used to develop a predictive model for early diagnosis of anorexia. It was based on the concentration of six elements (Zn, Fe, Mg, Cu, Ca, and Mn) and the age extracted from 90 cases. Compared with the results obtained from two other classifiers, partial least squares (PLS) and back-propagation neural network (BPNN), the SVM method exhibited the best whole performance. The accuracies for the test set by PLS, BPNN, and SVM methods were 52%, 65%, and 87%, respectively. Moreover, the models we proposed could also provide some insight into what factors were related to anorexia.

QSAR study of natural, synthetic and environmental endocrine disrupting compounds for binding to the androgen receptor

A large data set of 146 natural, synthetic and environmental chemicals belonging to a broad range of structural classes have been tested for their relative binding affinity (expressed as log (RBA)) to the androgen receptor (AR). These chemicals commonly termed endocrine disrupting compounds (EDCs) present a variety of adverse effects in humans and animals. As assays for binding affinity remains a time-consuming task, it is important to develop predictive methods. In this work, quantitative structure-activity relationships (QSARs) were determined using three methods, multiple linear regression (MLR), radical basis function neural network (RBFNN) and support vector machine (SVM). Five descriptors, accounting for hydrogen-bonding interaction, distribution of atomic charges and molecular branching degree, were selected from a heuristic method to build predictive QSAR models. Comparison of the results obtained from three models showed that the SVM method exhibited the best overall performances, with a RMS error of 0.54 log (RBA) units for the training set, 0.59 for the test set, and 0.55 for the whole set. Moreover, six linear QSAR models were constructed for some specific families based on their chemical structures. These predictive toxicology models, should be useful to rapidly identify potential androgenic endocrine disrupting compounds.

Study of probabilistic neural networks to classify the active compounds in medicinal plants

Probabilistic neural networks (PNNs) were utilized for the classifications of 102 active compounds from diverse medicinal plants with anticancer activity against human rhinopharyngocele cell line KB. Molecular descriptors calculated from structure alone were used to represent molecular structures. A subset of the calculated descriptors selected using factor correlation analysis and forward stepwise regression was used to construct the prediction models. Linear discriminant analysis (LDA) was also utilized to construct the classification model to compare the results with those obtained by PNNs. The accuracy of the training set, the cross-validation set, and the test set given by PNNs and LDA were 100, 92.3, 90.9% and 71.8, 92.3, 54.5%, respectively, which indicated that the results obtained by PNNs agree well with the experimental values of these compounds and also revealed the superiority of PNNs over LDA approach for the classification of anticancer activities of compounds. The models built in this work would be of potential help in the design of novel and more potent anticancer agents.

3D QSAR studies on antimalarial alkoxylated and hydroxylated chalcones by CoMFA and CoMSIA

The 3D QSAR analyses of antimalarial alkoxylated and hydroxylated chalcones were first conducted by Comparative molecular field analysis (CoMFA) and Comparative similarity indices analysis (CoMSIA) to determine the factors required for the activity of these compounds. Satisfactory results were obtained after performing a leave-one-out (LOO) cross-validation study with cross-validation q(2) and conventional r(2) values of 0.740 and 0.972 by the CoMFA model, 0.714 and 0.976 by the CoMSIA model, respectively. The results provided the tools for predicting the affinity of related compounds, and for guiding the design and synthesis of novel and more potent antimalarial agents.

Quantitative Prediction of logk of Peptides in High-Performance Liquid Chromatography Based on Molecular Descriptors by Using the Heuristic Method and Support Vector Machine

A new method support vector machine (SVM) and the heuristic method (HM) were used to develop the nonlinear and linear models between the capacity factor (logk) and seven molecular descriptors of 75 peptides for the first time. The molecular descriptors representing the structural features of the compounds only included the constitutional and topological descriptors, which can be obtained easily without optimizing the structure of the molecule. The seven molecular descriptors selected by the heuristic method in CODESSA were used as inputs for SVM. The results obtained by SVM were compared with those obtained by the heuristic method. The prediction result of the SVM model is better than that of heuristic method. For the test set, a predictive correlation coefficient R = 0.9801 and root-mean-square error of 0.1523 were obtained. The prediction results are in very good agreement with the experimental values. But the linear model of the heuristic method is easier to understand and ready to use for a chemist. This paper provided a new and effective method for predicting the chromatography retention of peptides and some insight into the structural features which are related to the capacity factor of peptides.

QSAR Models for the Prediction of Binding Affinities to Human Serum Albumin Using the Heuristic Method and a Support Vector Machine

The binding affinities to human serum albumin for 94 diverse drugs and drug-like compounds were modeled with the descriptors calculated from the molecular structure alone using a quantitative structure-activity relationship (QSAR) technique. The heuristic method (HM) and support vector machine (SVM) were utilized to construct the linear and nonlinear prediction models, leading to a good correlation coefficient (R2) of 0.86 and 0.94 and root-mean-square errors (rms) of 0.212 and 0.134 albumin drug binding affinity units, respectively. Furthermore, the models were evaluated by a 10 compound external test set, yielding R2 of 0.71 and 0.89 and rms error of 0.430 and 0.222. The specific information described by the heuristic linear model could give some insights into the factors that are likely to govern the binding affinity of the compounds and be used as an aid to the drug design process; however, the prediction results of the nonlinear SVM model seem to be better than that of the HM.

Study of the Quantitative Structure-Mobility Relationship of Carboxylic Acids in Capillary Electrophoresis Based on Support Vector Machines

The support vector machines (SVM), as a novel type of learning machine, were used to develop a quantitative structure-mobility relationship (QSMR) model of 58 aliphatic and aromatic carboxylic acids based on molecular descriptors calculated from the structure alone. Multiple linear regression (MLR) and radial basis function neural networks (RBFNNs) were also utilized to construct the linear and the nonlinear model to compare with the results obtained by SVM. The root-mean-square errors in absolute mobility predictions for the whole data set given by MLR, RBFNNs, and SVM were 1.530, 1.373, and 0.888 mobility units (10(-5) cm(2) S(-1) V(-1)), respectively, which indicated that the prediction result agrees well with the experimental values of these compounds and also revealed the superiority of SVM over MLR and RBFNNs models for the prediction of the absolute mobility of carboxylic acids. Moreover, the models we proposed could also provide some insight into what structural features are related to the absolute mobility of aliphatic and aromatic carboxylic acids.

An Accurate QSPR Study of O−H Bond Dissociation Energy in Substituted Phenols Based on Support Vector Machines

The support vector machine (SVM), as a novel type of learning machine, was used to develop a Quantitative Structure-Property Relationship (QSPR) model of the O-H bond dissociation energy (BDE) of 78 substituted phenols. The six descriptors calculated solely from the molecular structures of compounds selected by forward stepwise regression were used as inputs for the SVM model. The root-mean-square (rms) errors in BDE predictions for the training, test, and overall data sets were 3.808, 3.320, and 3.713 BDE units (kJ mol(-1)), respectively. The results obtained by Gaussian-kernel SVM were much better than those obtained by multiple linear regression, radial basis function neural networks, linear-kernel SVM, and other QSPR approaches.