Dataset Information

Flourishing deep-sea AAP bacteria detected by flow cytometric sorting and molecular analysis.

ABSTRACT: Pigmented bacteria cells, including aerobic anoxygenic phototrophic (AAP) bacteria, contribute significantly to secondary production and aquatic carbon cycling but their distribution in the deep sea is still not well understood, especially in the South China Sea. In this study, microscopic, flow cytometric, and molecular analyses were carried out to investigate the abundance and diversity of AAP bacteria at seven stations in the South China Sea. The results revealed the existence of bacteriochlorophyll-containing bacteria below 500 m from two of seven stations. Flow cytometric analysis detected red and infra-red fluorescence under blue (488 nm) light excitation from fluorescent cells. Blue light-excited red fluorescence of these cells from the 1000 m depth at station E403 were verified using epifluorescence microscopy. Based on fluorescence and side scatter features, fluorescent cells were sorted and subjected to molecular analysis. DNA was extracted from these sorted cells from both stations for PCR amplification using 16S rDNA primers. Sequencing of the PCR products showed that the sorted cells from the 1000 m depth at station E403 belonged to the genus Porphyrobacter. The cell population sorted from 500 m at station E703 contained Sphingomonas and a Methylobacterium-like taxon. All these three taxa belong to aerobic anoxygenic phototrophic alpha-proteobacteria. Using flow cytometric analysis, we found that the abundance of Porphyrobacter sp. at 1000 m was 2.71-2.95×104 cells mL-1 whereas cell counts of Sphingomonas sp. and Methylobacterium at 500 m were about 3.75-4.12×105 cells mL-1. These results indicate that albeit not ubiquitous in deep water, bacteriochlorophyll-containing bacteria can be abundant in the deep-sea aphotic zone.

SUBMITTER: Qiu D

PROVIDER: S-EPMC6583994 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Flourishing deep-sea AAP bacteria detected by flow cytometric sorting and molecular analysis.

Qiu Dajun D Huang Liangmin L Liu Xin X Lin Senjie S

PloS one 20190619 6

Pigmented bacteria cells, including aerobic anoxygenic phototrophic (AAP) bacteria, contribute significantly to secondary production and aquatic carbon cycling but their distribution in the deep sea is still not well understood, especially in the South China Sea. In this study, microscopic, flow cytometric, and molecular analyses were carried out to investigate the abundance and diversity of AAP bacteria at seven stations in the South China Sea. The results revealed the existence of bacteriochlo ...[more]

PMID: 31216335

Similar Datasets

Project description:BackgroundFlow cytometric sorting can be used to separate sperm based on sex chromosome content. Differential fluorescence emitted by stained X- vs. Y-chromosome-bearing sperm enables sorting and collection of samples enriched in either X- or Y-bearing sperm for use to influence the likelihood that the offspring will be a particular sex. Herein we report the effectiveness of flow cytometric sorting of human sperm and its use in human ART procedures.MethodsThis prospective, observational cohort study of the series of subjects treated with flow cytometrically sorted human sperm was conducted at investigational sites at two private reproductive centers. After meeting inclusion criteria, married couples (n = 4993) enrolled to reduce the likelihood of sex-linked or sex-limited disease in future children (n = 383) or to balance the sex ratio of their children (n = 4610). Fresh or frozen-thawed semen was processed and recovered sperm were stained with Hoechst 33342 and sorted by flow cytometry (n = 7718) to increase the percentage of X-bearing sperm (n = 5635) or Y-bearing sperm (n = 2083) in the sorted specimen. Sorted sperm were used for IUI (n = 4448) and IVF/ICSI (n = 2957). Measures of effectiveness were the percentage of X- and Y-bearing sperm in sorted samples, determined by fluorescence in situ hybridization, sex of babies born, IVF/ICSI fertilization- and cleavage rates, and IUI, IVF/ICSI, FET pregnancy rates and miscarriage rates.ResultsSorted specimens averaged 87.7 ± 5.0% X-bearing sperm after sorting for X and 74.3 ± 7.0% Y-bearing sperm after sorting for Y. Seventy-three percent of sorts were for girls. For babies born, 93.5% were females and 85.3% were males after sorting for X- and Y-bearing sperm, respectively. IUI, IVF/ICSI, and FET clinical pregnancy rates were 14.7%, 30.8%, and 32.1%, respectively; clinical miscarriage rates were 15.5%, 10.2%, and 12.7%.ConclusionsFlow cytometric sorting of human sperm shifted the X:Y sperm ratio. IUI, IVF/ICSI and FET outcomes were consistent with unimpaired sperm function. Results provide evidence supporting the effectiveness of flow cytometric sorting of human sperm for use as a preconception method of influencing a baby's sex.Trial registrationNCT00865735 (ClinicalTrials.gov).

Project description:BackgroundMalaria remains a major cause of morbidity and mortality worldwide. Flow cytometry-based assays that take advantage of fluorescent protein (FP)-expressing malaria parasites have proven to be valuable tools for quantification and sorting of specific subpopulations of parasite-infected red blood cells. However, identification of rare subpopulations of parasites using green fluorescent protein (GFP) labelling is complicated by autofluorescence (AF) of red blood cells and low signal from transgenic parasites. It has been suggested that cell sorting yield could be improved by using filters that precisely match the emission spectrum of GFP.MethodsDetection of transgenic Plasmodium falciparum parasites expressing either tdTomato or GFP was performed using a flow cytometer with interchangeable optical filters. Parasitaemia was evaluated using different optical filters and, after optimization of optics, the GFP-expressing parasites were sorted and analysed by microscopy after cytospin preparation and by imaging cytometry.ResultsA new approach to evaluate filter performance in flow cytometry using two-dimensional dot blot was developed. By selecting optical filters with narrow bandpass (BP) and maximum position of filter emission close to GFP maximum emission in the FL1 channel (510/20, 512/20 and 517/20; dichroics 502LP and 466LP), AF was markedly decreased and signal-background improve dramatically. Sorting of GFP-expressing parasite populations in infected red blood cells at 90 or 95% purity with these filters resulted in 50-150% increased yield when compared to the standard filter set-up. The purity of the sorted population was confirmed using imaging cytometry and microscopy of cytospin preparations of sorted red blood cells infected with transgenic malaria parasites.DiscussionFilter optimization is particularly important for applications where the FP signal and percentage of positive events are relatively low, such as analysis of parasite-infected samples with in the intention of gene-expression profiling and analysis. The approach outlined here results in substantially improved yield of GFP-expressing parasites, and requires decreased sorting time in comparison to standard methods. It is anticipated that this protocol will be useful for a wide range of applications involving rare events.

Project description:BackgroundFlow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients' ventilatory demand due to an insufficient airflow and/or a high inspiratory effort, and it is usually identified by visual inspection of airway pressure waveform. Clinical diagnosis is cumbersome and prone to underdiagnosis, being an opportunity for artificial intelligence. Our objective is to develop a supervised artificial intelligence algorithm for identifying airway pressure deformation during square-flow assisted ventilation and patient-triggered breaths.MethodsMulticenter, observational study. Adult critically ill patients under mechanical ventilation > 24 h on square-flow assisted ventilation were included. As the reference, 5 intensive care experts classified airway pressure deformation severity. Convolutional neural network and recurrent neural network models were trained and evaluated using accuracy, precision, recall and F1 score. In a subgroup of patients with esophageal pressure measurement (ΔPes), we analyzed the association between the intensity of the inspiratory effort and the airway pressure deformation.Results6428 breaths from 28 patients were analyzed, 42% were classified as having normal-mild, 23% moderate, and 34% severe airway pressure deformation. The accuracy of recurrent neural network algorithm and convolutional neural network were 87.9% [87.6-88.3], and 86.8% [86.6-87.4], respectively. Double triggering appeared in 8.8% of breaths, always in the presence of severe airway pressure deformation. The subgroup analysis demonstrated that 74.4% of breaths classified as severe airway pressure deformation had a ΔPes > 10 cmH2O and 37.2% a ΔPes > 15 cmH2O.ConclusionsRecurrent neural network model appears excellent to identify airway pressure deformation due to flow starvation. It could be used as a real-time, 24-h bedside monitoring tool to minimize unrecognized periods of inappropriate patient-ventilator interaction.

Dataset Information

Flourishing deep-sea AAP bacteria detected by flow cytometric sorting and molecular analysis.

Publications

Flourishing deep-sea AAP bacteria detected by flow cytometric sorting and molecular analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets