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September 22, 2019

Automated broad range molecular detection of bacteria in clinical samples.

Molecular detection methods, such as quantitative PCR (qPCR), have found their way into clinical microbiology laboratories for the detection of an array of pathogens. Most routinely used methods, however, are directed at specific species. Thus, anything that is not explicitly searched for will be missed. This greatly limits the flexibility and universal application of these techniques. We investigated the application of a rapid universal bacterial molecular identification method, IS-pro, to routine patient samples received in a clinical microbiology laboratory. IS-pro is a eubacterial technique based on the detection and categorization of 16S-23S rRNA gene interspace regions with lengths that are specific for each microbial species. As this is an open technique, clinicians do not need to decide in advance what to look for. We compared routine culture to IS-pro using 66 samples sent in for routine bacterial diagnostic testing. The samples were obtained from patients with infections in normally sterile sites (without a resident microbiota). The results were identical in 20 (30%) samples, IS-pro detected more bacterial species than culture in 31 (47%) samples, and five of the 10 culture-negative samples were positive with IS-pro. The case histories of the five patients from whom these culture-negative/IS-pro-positive samples were obtained suggest that the IS-pro findings are highly clinically relevant. Our findings indicate that an open molecular approach, such as IS-pro, may have a high added value for clinical practice. Copyright © 2016, American Society for Microbiology. All Rights Reserved.


September 22, 2019

Bacteroides dorei dominates gut microbiome prior to autoimmunity in Finnish children at high risk for type 1 diabetes.

The incidence of the autoimmune disease, type 1 diabetes (T1D), has increased dramatically over the last half century in many developed countries and is particularly high in Finland and other Nordic countries. Along with genetic predisposition, environmental factors are thought to play a critical role in this increase. As with other autoimmune diseases, the gut microbiome is thought to play a potential role in controlling progression to T1D in children with high genetic risk, but we know little about how the gut microbiome develops in children with high genetic risk for T1D. In this study, the early development of the gut microbiomes of 76 children at high genetic risk for T1D was determined using high-throughput 16S rRNA gene sequencing. Stool samples from children born in the same hospital in Turku, Finland were collected at monthly intervals beginning at 4-6 months after birth until 2.2 years of age. Of those 76 children, 29 seroconverted to T1D-related autoimmunity (cases) including 22 who later developed T1D, the remaining 47 subjects remained healthy (controls). While several significant compositional differences in low abundant species prior to seroconversion were found, one highly abundant group composed of two closely related species, Bacteroides dorei and Bacteroides vulgatus, was significantly higher in cases compared to controls prior to seroconversion. Metagenomic sequencing of samples high in the abundance of the B. dorei/vulgatus group before seroconversion, as well as longer 16S rRNA sequencing identified this group as Bacteroides dorei. The abundance of B. dorei peaked at 7.6 months in cases, over 8 months prior to the appearance of the first islet autoantibody, suggesting that early changes in the microbiome may be useful for predicting T1D autoimmunity in genetically susceptible infants. The cause of increased B. dorei abundance in cases is not known but its timing appears to coincide with the introduction of solid food.


September 22, 2019

Fungal ITS1 deep-sequencing strategies to reconstruct the composition of a 26-species community and evaluation of the gut mycobiota of healthy Japanese individuals.

The study of mycobiota remains relatively unexplored due to the lack of sufficient available reference strains and databases compared to those of bacterial microbiome studies. Deep sequencing of Internal Transcribed Spacer (ITS) regions is the de facto standard for fungal diversity analysis. However, results are often biased because of the wide variety of sequence lengths in the ITS regions and the complexity of high-throughput sequencing (HTS) technologies. In this study, a curated ITS database, ntF-ITS1, was constructed. This database can be utilized for the taxonomic assignment of fungal community members. We evaluated the efficacy of strategies for mycobiome analysis by using this database and characterizing a mock fungal community consisting of 26 species representing 15 genera using ITS1 sequencing with three HTS platforms: Illumina MiSeq (MiSeq), Ion Torrent Personal Genome Machine (IonPGM), and Pacific Biosciences (PacBio). Our evaluation demonstrated that PacBio’s circular consensus sequencing with greater than 8 full-passes most accurately reconstructed the composition of the mock community. Using this strategy for deep-sequencing analysis of the gut mycobiota in healthy Japanese individuals revealed two major mycobiota types: a single-species type composed of Candida albicans or Saccharomyces cerevisiae and a multi-species type. In this study, we proposed the best possible processing strategies for the three sequencing platforms, of which, the PacBio platform allowed for the most accurate estimation of the fungal community. The database and methodology described here provide critical tools for the emerging field of mycobiome studies.


September 22, 2019

Investigating bacterial population structure and dynamics in traditional koumiss from Inner Mongolia using single molecule real-time sequencing.

Koumiss is considered as a complete dairy product high in nutrients and with medicinal properties. The bacterial communities involved in production of koumiss play a crucial role in the fermentation cycle. To reveal bacterial biodiversity in koumiss and the dynamics of succession in bacterial populations during fermentation, 22 samples were collected from 5 sampling sites and the full length of the 16S ribosomal RNA genes sequenced using single molecule real-time sequencing technology. One hundred forty-eight species were identified from 82 bacterial genera and 8 phyla. These results suggested that the structural difference in the bacterial community could be attributed to geographical location. The most significant difference in bacterial composition occurred in samples from group D compared with other groups. The sampling location of group D was distant from the city and maintained the primitive local nomadic life. The dynamics of succession in bacterial communities showed that Lactobacillus helveticus increased in abundance from 0 to 9h and reached its peak at 9h and then decreased. In contrast, Enterococcus faecalis, Enterococcus durans, and Enterococcus casseliflavus increased gradually throughout the fermentation process, and reached a maximum after 24h. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.


September 22, 2019

Analyses of intestinal microbiota: culture versus sequencing.

Analyzing human as well as animal microbiota composition has gained growing interest because structural components and metabolites of microorganisms fundamentally influence all aspects of host physiology. Originally dominated by culture-dependent methods for exploring these ecosystems, the development of molecular techniques such as high throughput sequencing has dramatically increased our knowledge. Because many studies of the microbiota are based on the bacterial 16S ribosomal RNA (rRNA) gene targets, they can, at least in principle, be compared to determine the role of the microbiome composition for developmental processes, host metabolism, and physiology as well as different diseases. In our review, we will summarize differences and pitfalls in current experimental protocols, including all steps from nucleic acid extraction to bioinformatical analysis which may produce variation that outweighs subtle biological differences. Future developments, such as integration of metabolomic, transcriptomic, and metagenomic data sets and standardization of the procedures, will be discussed. © The Author 2015. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.


September 22, 2019

Alternative splice variants of AID are not stoichiometrically present at the protein level in chronic lymphocytic leukemia

Activation-induced deaminase (AID) is a DNA-mutating enzyme that mediates class-switch recombination as well as somatic hypermutation of antibody genes in B cells. Due to off-target activity, AID is implicated in lymphoma development by introducing genome-wide DNA damage and initiating chromosomal translocations such as c-myc/IgH. Several alternative splice transcripts of AID have been reported in activated B cells as well as malignant B cells such as chronic lymphocytic leukemia (CLL). As most commercially available antibodies fail to recognize alternative splice variants, their abundance in vivo, and hence their biological significance, has not been determined. In this study, we assessed the protein levels of AID splice isoforms by introducing an AID splice reporter construct into cell lines and primary CLL cells from patients as well as from WT and TCL1(tg) C57BL/6 mice (where TCL1 is T-cell leukemia/lymphoma 1). The splice construct is 5′-fused to a GFP-tag, which is preserved in all splice isoforms and allows detection of translated protein. Summarizing, we show a thorough quantification of alternatively spliced AID transcripts and demonstrate that the corresponding protein abundances, especially those of splice variants AID-ivs3 and AID-?E4, are not stoichiometrically equivalent. Our data suggest that enhanced proteasomal degradation of low-abundance proteins might be causative for this discrepancy. © 2013 The Authors. European Journal of Immunology published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


September 22, 2019

Somatic APP gene recombination in Alzheimer’s disease and normal neurons.

The diversity and complexity of the human brain are widely assumed to be encoded within a constant genome. Somatic gene recombination, which changes germline DNA sequences to increase molecular diversity, could theoretically alter this code but has not been documented in the brain, to our knowledge. Here we describe recombination of the Alzheimer’s disease-related gene APP, which encodes amyloid precursor protein, in human neurons, occurring mosaically as thousands of variant ‘genomic cDNAs’ (gencDNAs). gencDNAs lacked introns and ranged from full-length cDNA copies of expressed, brain-specific RNA splice variants to myriad smaller forms that contained intra-exonic junctions, insertions, deletions, and/or single nucleotide variations. DNA in situ hybridization identified gencDNAs within single neurons that were distinct from wild-type loci and absent from non-neuronal cells. Mechanistic studies supported neuronal ‘retro-insertion’ of RNA to produce gencDNAs; this process involved transcription, DNA breaks, reverse transcriptase activity, and age. Neurons from individuals with sporadic Alzheimer’s disease showed increased gencDNA diversity, including eleven mutations known to be associated with familial Alzheimer’s disease that were absent from healthy neurons. Neuronal gene recombination may allow ‘recording’ of neural activity for selective ‘playback’ of preferred gene variants whose expression bypasses splicing; this has implications for cellular diversity, learning and memory, plasticity, and diseases of the human brain.


September 22, 2019

Resistance to ceftazidime-avibactam in Klebsiella pneumoniae due to porin mutations and the increased expression of KPC-3.

We reported the first clinical case of a ceftazidime-avibactam resistant KPC-3-producing Klebsiella pneumoniae (1), from a patient with no history of ceftazidime-avibactam therapy. We now present data documenting mechanisms of ceftazidime-avibactam resistance in this isolate. Whole-genome sequencing (WGS) was performed on two isolates: KP1245 (ceftazidime-avibactam MIC, 4 µg/ml; from blood on hospital day 1; referred to as isolate 1 in our previous report [1]) and KP1244 (ceftazidime-avibactam MIC, 32 µg/ml; from blood on hospital day 2; referred to as isolate 2 in our previous report [2]), using MiSeq (Illumina, San Diego, CA) and PacBio RSII (Menlo Park, CA) systems (2). The in silico multilocus sequence type (ST) was ST258. Single nucleotide polymorphism (SNP) analysis revealed 17 SNPs between KP1245 and KP1244, indicating that the isolates were related but that significant diversity existed in this patient (2). Nonsynonymous mutations are shown in Table 1; the most striking of these is in the OmpK36 porin gene. KP1244 contained a missense mutation predicted to encode a T333N mutation. Both isolates also harbored a mutation predicted to encode R191L in OmpK36 and had a nonfunctional OmpK35, due to a frameshift mutation that truncated the protein at amino acid 42, common to K. pneumoniae ST258 (3). Association between mutations in ompK36 and elevated ceftazidime-avibactam MICs has been shown previously (4). However, T333N, found in one of the ß-sheet domains of the OmpK36 subunit, has not been described in K. pneumoniae; as such, further validation is required to confirm the role of the OmpK36 mutation in this isolate’s ceftazidime-avibactam resistance phenotype.


September 22, 2019

Assessment of the physicochemical properties and bacterial composition of Lactobacillus plantarum and Enterococcus faecium-fermented Astragalus membranaceus using single molecule, real-time sequencing technology.

We investigated if fermentation with probiotic cultures could improve the production of health-promoting biological compounds in Astragalus membranaceus. We tested the probiotics Enterococcus faecium, Lactobacillus plantarum and Enterococcus faecium?+?Lactobacillus plantarum and applied PacBio single molecule, real-time sequencing technology (SMRT) to evaluate the quality of Astragalus fermentation. We found that the production rates of acetic acid, methylacetic acid, aethyl acetic acid and lactic acid using E. faecium?+?L. plantarum were 1866.24?mg/kg on day 15, 203.80?mg/kg on day 30, 996.04?mg/kg on day 15, and 3081.99?mg/kg on day 20, respectively. Other production rates were: polysaccharides, 9.43%, 8.51%, and 7.59% on day 10; saponins, 19.6912?mg/g, 21.6630?mg/g and 20.2084?mg/g on day 15; and flavonoids, 1.9032?mg/g, 2.0835?mg/g, and 1.7086?mg/g on day 20 using E. faecium, L. plantarum and E. faecium?+?L. plantarum, respectively. SMRT was used to analyze microbial composition, and we found that E. faecium and L. plantarum were the most prevalent species after fermentation for 3 days. E. faecium?+?L. plantarum gave more positive effects than single strains in the Astragalus solid state fermentation process. Our data demonstrated that the SMRT sequencing platform is applicable to quality assessment of Astragalus fermentation.


September 22, 2019

The human microbiome and understanding the 16S rRNA gene in translational nursing science.

As more is understood regarding the human microbiome, it is increasingly important for nurse scientists and healthcare practitioners to analyze these microbial communities and their role in health and disease. 16S rRNA sequencing is a key methodology in identifying these bacterial populations that has recently transitioned from use primarily in research to having increased utility in clinical settings.The objectives of this review are to (a) describe 16S rRNA sequencing and its role in answering research questions important to nursing science; (b) provide an overview of the oral, lung, and gut microbiomes and relevant research; and (c) identify future implications for microbiome research and 16S sequencing in translational nursing science.Sequencing using the 16S rRNA gene has revolutionized research and allowed scientists to easily and reliably characterize complex bacterial communities. This type of research has recently entered the clinical setting, one of the best examples involving the use of 16S sequencing to identify resistant pathogens, thereby improving the accuracy of bacterial identification in infection control. Clinical microbiota research and related requisite methods are of particular relevance to nurse scientists-individuals uniquely positioned to utilize these techniques in future studies in clinical settings.


September 22, 2019

Localized electron transfer rates and microelectrode-based enrichment of microbial communities within a phototrophic microbial mat.

Phototrophic microbial mats frequently exhibit sharp, light-dependent redox gradients that regulate microbial respiration on specific electron acceptors as a function of depth. In this work, a benthic phototrophic microbial mat from Hot Lake, a hypersaline, epsomitic lake located near Oroville in north-central Washington, was used to develop a microscale electrochemical method to study local electron transfer processes within the mat. To characterize the physicochemical variables influencing electron transfer, we initially quantified redox potential, pH, and dissolved oxygen gradients by depth in the mat under photic and aphotic conditions. We further demonstrated that power output of a mat fuel cell was light-dependent. To study local electron transfer processes, we deployed a microscale electrode (microelectrode) with tip size ~20 µm. To enrich a subset of microorganisms capable of interacting with the microelectrode, we anodically polarized the microelectrode at depth in the mat. Subsequently, to characterize the microelectrode-associated community and compare it to the neighboring mat community, we performed amplicon sequencing of the V1-V3 region of the 16S gene. Differences in Bray-Curtis beta diversity, illustrated by large changes in relative abundance at the phylum level, suggested successful enrichment of specific mat community members on the microelectrode surface. The microelectrode-associated community exhibited substantially reduced alpha diversity and elevated relative abundances of Prosthecochloris, Loktanella, Catellibacterium, other unclassified members of Rhodobacteraceae, Thiomicrospira, and Limnobacter, compared with the community at an equivalent depth in the mat. Our results suggest that local electron transfer to an anodically polarized microelectrode selected for a specific microbial population, with substantially more abundance and diversity of sulfur-oxidizing phylotypes compared with the neighboring mat community.


September 22, 2019

Quantitative profiling of Drosophila melanogaster Dscam1 isoforms reveals no changes in splicing after bacterial exposure.

The hypervariable Dscam1 (Down syndrome cell adhesion molecule 1) gene can produce thousands of different ectodomain isoforms via mutually exclusive alternative splicing. Dscam1 appears to be involved in the immune response of some insects and crustaceans. It has been proposed that the diverse isoforms may be involved in the recognition of, or the defence against, diverse parasite epitopes, although evidence to support this is sparse. A prediction that can be generated from this hypothesis is that the gene expression of specific exons and/or isoforms is influenced by exposure to an immune elicitor. To test this hypothesis, we for the first time, use a long read RNA sequencing method to directly investigate the Dscam1 splicing pattern after exposing adult Drosophila melanogaster and a S2 cell line to live Escherichia coli. After bacterial exposure both models showed increased expression of immune-related genes, indicating that the immune system had been activated. However there were no changes in total Dscam1 mRNA expression. RNA sequencing further showed that there were no significant changes in individual exon expression and no changes in isoform splicing patterns in response to bacterial exposure. Therefore our studies do not support a change of D. melanogaster Dscam1 isoform diversity in response to live E. coli. Nevertheless, in future this approach could be used to identify potentially immune-related Dscam1 splicing regulation in other host species or in response to other pathogens.


September 22, 2019

Active microorganisms in forest soils differ from the total community yet are shaped by the same environmental factors: the influence of pH and soil moisture.

Predicting the impact of environmental change on soil microbial functions requires an understanding of how environmental factors shape microbial composition. Here, we investigated the influence of environmental factors on bacterial and fungal communities across an expanse of northern hardwood forest in Michigan, USA, which spans a 500-km regional climate gradient. We quantified soil microbial community composition using high-throughput DNA sequencing on coextracted rDNA (i.e. total community) and rRNA (i.e. active community). Within both bacteria and fungi, total and active communities were compositionally distinct from one another across the regional gradient (bacteria P = 0.01; fungi P < 0.01). Taxonomically, the active community was a subset of the total community. Compositional differences between total and active communities reflected changes in the relative abundance of dominant taxa. The composition of both the total and active microbial communities varied by site across the gradient (P < 0.01) and was shaped by differences in soil moisture, pH, SOM carboxyl content, as well as C and N concentration. Our study highlights the importance of distinguishing between metabolically active microorganisms and the total community, and emphasizes that the same environmental factors shape the total and active communities of bacteria and fungi in this ecosystem.© FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.


September 22, 2019

MEGAN-LR: new algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs.

There are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing, and there is a need to adapt short read tools to long read datasets.We describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.All presented methods are implemented in the open source edition of MEGAN, and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.This article was reviewed by Nicola Segata together with Moreno Zolfo, Pete James Lockhart and Serghei Mangul.This work extends the applicability of the widely-used metagenomic analysis software MEGAN to long reads. Our study suggests that the presented LAST+MEGAN-LR pipeline is sufficiently fast and accurate.


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