Correction: Brain Meta-Transcriptomics from Harbor Seals to Infer the Role of the Microbiome and Virome in a Stranding Event.
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ABSTRACT:
SUBMITTER: Rosales SM
PROVIDER: S-EPMC4699895 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:Marine diseases are becoming more frequent, and tools for identifying pathogens and disease reservoirs are needed to help prevent and mitigate epizootics. Meta-transcriptomics provides insights into disease etiology by cataloguing and comparing sequences from suspected pathogens. This method is a powerful approach to simultaneously evaluate both the viral and bacterial communities, but few studies have applied this technique in marine systems. In 2009 seven harbor seals, Phoca vitulina, stranded along the California coast from a similar brain disease of unknown cause of death (UCD). We evaluated the differences between the virome and microbiome of UCDs and harbor seals with known causes of death. Here we determined that UCD stranded animals had no viruses in their brain tissue. However, in the bacterial community, we identified Burkholderia and Coxiella burnetii as important pathogens associated with this stranding event. Burkholderia were 100% prevalent and ~2.8 log2 fold more abundant in the UCD animals. Further, while C. burnetii was found in only 35.7% of all samples, it was highly abundant (~94% of the total microbial community) in a single individual. In this harbor seal, C. burnetii showed high transcription rates of invading and translation genes, implicating it in the pathogenesis of this animal. Based on these data we propose that Burkholderia taxa and C. burnetii are potentially important opportunistic neurotropic pathogens in UCD stranded harbor seals.
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Project description:Brain meta-transcriptomics from harbor seals to infer the role of the microbiome and virome in a stranding event
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Project description:Head motion degrades image quality and causes erroneous parameter estimates in tracer kinetic modeling in brain PET studies. Existing motion correction methods include frame-based image registration (FIR) and correction using real-time hardware-based motion tracking (HMT) information. However, FIR cannot correct for motion within 1 predefined scan period, and HMT is not readily available in the clinic since it typically requires attaching a tracking device to the patient. In this study, we propose a motion correction framework with a data-driven algorithm, that is, using the PET raw data itself, to address these limitations. Methods: We propose a data-driven algorithm, centroid of distribution (COD), to detect head motion. In COD, the central coordinates of the line of response of all events are averaged over 1-s intervals to generate a COD trace. A point-to-point change in the COD trace in 1 direction that exceeded a user-defined threshold was defined as a time point of head motion, which was followed by manually adding additional motion time points. All the frames defined by such time points were reconstructed without attenuation correction and rigidly registered to a reference frame. The resulting transformation matrices were then used to perform the final motion-compensated reconstruction. We applied the new COD framework to 23 human dynamic datasets, all containing large head motion, with 18F-FDG (n = 13) and 11C-UCB-J ((R)-1-((3-(11C-methyl-11C)pyridin-4-yl)methyl)-4-(3,4,5-trifluorophenyl)pyrrolidin-2-one) (n = 10) and compared its performance with FIR and with HMT using Vicra (an optical HMT device), which can be considered the gold standard. Results: The COD method yielded a 1.0% ± 3.2% (mean ± SD across all subjects and 12 gray matter regions) SUV difference for 18F-FDG (3.7% ± 5.4% for 11C-UCB-J) compared with HMT, whereas no motion correction (NMC) and FIR yielded -15.7% ± 12.2% (-20.5% ± 15.8%) and -4.7% ± 6.9% (-6.2% ± 11.0%), respectively. For 18F-FDG dynamic studies, COD yielded differences of 3.6% ± 10.9% in K i value as compared with HMT, whereas NMC and FIR yielded -18.0% ± 39.2% and -2.6% ± 19.8%, respectively. For 11C-UCB-J, COD yielded 3.7% ± 5.2% differences in V T compared with HMT, whereas NMC and FIR yielded -20.0% ± 12.5% and -5.3% ± 9.4%, respectively. Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR and achieved comparable or even better performance than the Vicra HMT method in both static and dynamic studies.
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Project description:PET imaging of nonhuman primates (NHPs) requires correction of head motion if the subjects are scanned awake and their heads are unrestrained, because the NHPs move their heads faster and more frequently than human subjects. This work focuses on designing and validating 2 motion-correction algorithms for awake NHP brain PET imaging.Two motion-correction methods were implemented for awake NHP brain PET imaging: multiacquisition frame (MAF) and event-by-event (EBE). Motion data were acquired from an external motion-tracking device. The MAF method divides scan data into short subframes, reconstructs each subframe individually, and registers them to a reference orientation. This method suffers from residual intraframe motion and data loss when motion is large because a minimum frame duration is often required. The EBE method, previously implemented for a human brain scanner and adapted for a small-animal PET scanner in this work, eliminates intraframe motion and should have a best accuracy. We first evaluated the accuracy of both motion-correction methods with moving phantom scans. Both motion-correction methods were then applied to awake NHP brain PET studies with a gamma-aminobutyric acid A-benzodiazepine receptor ligand, (11)C-flumazenil, and the reconstructed images were compared with those from a motion-free anesthetized study.The phantom studies showed that EBE motion correction recovers the contrast (within 3%) similarly to the static study, whereas MAF motion correction using the standard algorithm setting showed a 25% reduction in contrast from the static case. In awake NHP brain PET imaging, EBE motion correction better recovers the fine structures than the MAF method, as compared with anesthetized studies.The large magnitude and frequency of NHP head motion suggests that EBE motion correction with accurate externally measured motion data can noticeably alleviate image blurring due to the intraframe motion in the MAF motion-correction method.
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Project description:Parametric images for dynamic positron emission tomography (PET) are typically generated by an indirect method, i.e. reconstructing a time series of emission images, then fitting a kinetic model to each voxel time activity curve. Alternatively, 'direct reconstruction', incorporates the kinetic model into the reconstruction algorithm itself, directly producing parametric images from projection data. Direct reconstruction has been shown to achieve parametric images with lower standard error than the indirect method. Here, we present direct reconstruction for brain PET using event-by-event motion correction of list-mode data, applied to two tracers. Event-by-event motion correction was implemented for direct reconstruction in the Parametric Motion-compensation OSEM List-mode Algorithm for Resolution-recovery reconstruction. The direct implementation was tested on simulated and human datasets with tracers [11C]AFM (serotonin transporter) and [11C]UCB-J (synaptic density), which follow the 1-tissue compartment model. Rigid head motion was tracked with the Vicra system. Parametric images of K 1 and distribution volume (V T??=??K 1/k 2) were compared to those generated by the indirect method by regional coefficient of variation (CoV). Performance across count levels was assessed using sub-sampled datasets. For simulated and real datasets at high counts, the two methods estimated K 1 and V T with comparable accuracy. At lower count levels, the direct method was substantially more robust to outliers than the indirect method. Compared to the indirect method, direct reconstruction reduced regional K 1 CoV by 35-48% (simulated dataset), 39-43% ([11C]AFM dataset) and 30-36% ([11C]UCB-J dataset) across count levels (averaged over regions at matched iteration); V T CoV was reduced by 51-58%, 54-60% and 30-46%, respectively. Motion correction played an important role in the dataset with larger motion: correction increased regional V T by 51% on average in the [11C]UCB-J dataset. Direct reconstruction of dynamic brain PET with event-by-event motion correction is achievable and dramatically more robust to noise in V T images than the indirect method.
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Project description:Hard ticks of the order Ixodidae serve as vectors for numerous human pathogens, including the causative agent of Lyme Disease Borrelia burgdorferi. Tick-associated microbes can influence pathogen colonization, offering the potential to inhibit disease transmission through engineering of the tick microbiota. Here, we investigate whether B. burgdorferi encounters abundant bacteria within the midgut of wild adult Ixodes scapularis, its primary vector. Through the use of controlled sequencing methods and confocal microscopy, we find that the majority of field-collected adult I. scapularis harbor limited internal microbial communities that are dominated by endosymbionts. A minority of I. scapularis ticks harbor abundant midgut bacteria and lack B. burgdorferi. We find that the lack of a stable resident midgut microbiota is not restricted to I. scapularis since extension of our studies to I. pacificus, Amblyomma maculatum, and Dermacentor spp showed similar patterns. Finally, bioinformatic examination of the B. burgdorferi genome revealed the absence of genes encoding known interbacterial interaction pathways, a feature unique to the Borrelia genus within the phylum Spirochaetes. Our results suggest that reduced selective pressure from limited microbial populations within ticks may have facilitated the evolutionary loss of genes encoding interbacterial competition pathways from Borrelia.
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