Novel Methanotrophs of the Family Methylococcaceae from Different Geographical Regions and Habitats

Terrestrial methane seeps and rice paddy fields are important ecosystems in the methane cycle. Methanotrophic bacteria in these ecosystems play a key role in reducing methane emission into the atmosphere. Here, we describe three novel methanotrophs, designated BRS-K6, GFS-K6 and AK-K6, which were recovered from three different habitats in contrasting geographic regions and ecosystems: waterlogged rice-field soil and methane seep pond sediments from Bangladesh; and warm spring sediments from Armenia. All isolates had a temperature range for growth of 8–35 °C (optimal 25–28 °C) and a pH range of 5.0–7.5 (optimal 6.4–7.0). 16S rRNA gene sequences showed that they were new gammaproteobacterial methanotrophs, which form a separate clade in the family Methylococcaceae. They fell into a cluster with thermotolerant and mesophilic growth tendency, comprising the genera Methylocaldum-Methylococcus-Methyloparacoccus-Methylogaea. So far, growth below 15 °C of methanotrophs from this cluster has not been reported. The strains possessed type I intracytoplasmic membranes. The genes pmoA, mxaF, cbbL, nifH were detected, but no mmoX gene was found. Each strain probably represents a novel species either belonging to the same novel genus or each may even represent separate genera. These isolates extend our knowledge of methanotrophic Gammaproteobacteria and their physiology and adaptation to different ecosystems

Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

<p>Abstract</p> <p>Background</p> <p>Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.</p> <p>Results</p> <p>A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of <it>Enterobacteriaceae</it>, non-fermenter and clinical relevant <it>Candida </it>species. The observed detection limits varied from 10 cells (e.g. <it>E. coli</it>) to 10⁵cells (<it>S. aureus</it>) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241).</p> <p>Conclusion</p> <p>The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.</p

Metabolic pathways inferred from a bacterial marker gene illuminate ecological changes across South Pacific frontal boundaries

Global oceanographic monitoring initiatives originally measured abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling programs. There is, however, a large knowledge gap on how to infer bacterial functions, the information sought by biogeochemists, ecologists, and modelers, from the bacterial taxonomic information (produced by bacterial marker gene surveys). Here, we provide a correlative understanding of how a bacterial marker gene (16S rRNA) can be used to infer latitudinal trends for metabolic pathways in global monitoring campaigns. From a transect spanning 7000 km in the South Pacific Ocean we infer ten metabolic pathways from 16S rRNA gene sequences and 11 corresponding metagenome samples, which relate to metabolic processes of primary productivity, temperature-regulated thermodynamic effects, coping strategies for nutrient limitation, energy metabolism, and organic matter degradation. This study demonstrates that low-cost, high-throughput bacterial marker gene data, can be used to infer shifts in the metabolic strategies at the community scale

Application of COMPOCHIP Microarray to Investigate the Bacterial Communities of Different Composts

A microarray spotted with 369 different 16S rRNA gene probes specific to microorganisms involved in the degradation process of organic waste during composting was developed. The microarray was tested with pure cultures, and of the 30,258 individual probe-target hybridization reactions performed, there were only 188 false positive (0.62%) and 22 false negative signals (0.07%). Labeled target DNA was prepared by polymerase chain reaction amplification of 16S rRNA genes using a Cy5-labeled universal bacterial forward primer and a universal reverse primer. The COMPOCHIP microarray was applied to three different compost types (green compost, manure mix compost, and anaerobic digestate compost) of different maturity (2, 8, and 16 weeks), and differences in the microorganisms in the three compost types and maturity stages were observed. Multivariate analysis showed that the bacterial composition of the three composts was different at the beginning of the composting process and became more similar upon maturation. Certain probes (targeting Sphingobacterium, Actinomyces, Xylella/Xanthomonas/ Stenotrophomonas, Microbacterium, Verrucomicrobia, Planctomycetes, Low G + C and Alphaproteobacteria) were more influential in discriminating between different composts. Results from denaturing gradient gel electrophoresis supported those of microarray analysis. This study showed that the COMPOCHIP array is a suitable tool to study bacterial communities in composts

Diatom Biogeography, Temporal Dynamics, and Links to Bacterioplankton across Seven Oceanographic Time-Series Sites Spanning the Australian Continent.

Diatom communities significantly influence ocean primary productivity and carbon cycling, but their spatial and temporal dynamics are highly heterogeneous and are governed by a complex diverse suite of abiotic and biotic factors. We examined the seasonal and biogeographical dynamics of diatom communities in Australian coastal waters using amplicon sequencing data (18S-16S rRNA gene) derived from a network of oceanographic time-series spanning the Australian continent. We demonstrate that diatom community composition in this region displays significant biogeography, with each site harbouring distinct community structures. Temperature and nutrients were identified as the key environmental contributors to differences in diatom communities at all sites, collectively explaining 21% of the variability observed in diatoms assemblages. However, specific groups of bacteria previously implicated in mutualistic ecological interactions with diatoms (Rhodobacteraceae, Flavobacteriaceae and Alteromonadaceae) also explained a further 4% of the spatial dynamics observed in diatom community structure. We also demonstrate that the two most temperate sites (Port Hacking and Maria Island) exhibited strong seasonality in diatom community and that at these sites, winter diatom communities co-occurred with higher proportion of Alteromonadaceae. In addition, we identified significant co-occurrence between specific diatom and bacterial amplicon sequence variants (ASVs), with members of the Roseobacter and Flavobacteria clades strongly correlated with some of the most abundant diatom genera (Skeletonema, Thalassiosira, and Cylindrotheca). We propose that some of these co-occurrences might be indicative of ecologically important interactions between diatoms and bacteria. Our analyses reveal that in addition to physico-chemical conditions (i.e., temperature, nutrients), the relative abundance of specific groups of bacteria appear to play an important role in shaping the spatial and temporal dynamics of marine diatom communities

ORMA: a tool for identification of species-specific variations in 16S rRNA gene and oligonucleotides design

16S rRNA gene is one of the preferred targets for resolving species phylogenesis issues in microbiological-related contexts. However, the identification of single-nucleotide variations capable of distinguishing a sequence among a set of homologous ones can be problematic. Here we present ORMA (Oligonucleotide Retrieving for Molecular Applications), a set of scripts for discriminating positions search and for performing the selection of high-quality oligonucleotide probes to be used in molecular applications. Two assays based on Ligase Detection Reaction (LDR) are presented. First, a new set of probe pairs on cyanobacteria 16S rRNA sequences of 18 different species was compared to that of a previous study. Then, a set of LDR probe pairs for the discrimination of 13 pathogens contaminating bovine milk was evaluated. The software determined more than 100 candidate probe pairs per dataset, from more than 300 16S rRNA sequences, in less than 5 min. Results demonstrated how ORMA improved the performance of the LDR assay on cyanobacteria, correctly identifying 12 out of 14 samples, and allowed the perfect discrimination among the 13 milk pathogenic-related species. ORMA represents a significant improvement from other contexts where enzyme-based techniques have been employed on already known mutations of a single base or on entire subsequences