DataSheet_1_Rapid duplex flap probe-based isothermal assay to identify the Cryptococcus neoformans and Cryptococcus gattii.docx

Cryptococcosis is a life-threatening invasive fungal infection with significantly increasing mortality worldwide, which is mainly caused by Cryptococcus neoformans and Cryptococcus gattii. These two species complexes have different epidemiological and clinical characteristics, indicating the importance of accurate differential diagnosis. However, the clinically used culture method and cryptococcal capsular antigen detection couldn’t achieve the above goals. Herein, we established a novel duplex flap probe-based isothermal assay to identify the Cryptococcus neoformans and Cryptococcus gattii within 1 hour. This assay combined the highly sensitive nucleic acid isothermal amplification and highly specific fluorescence probe method, which could effectively distinguish the sequence differences of the two species complexes using two different fluorescence flap probes in a single reaction system. This novel method showed excellent detection performance with sensitivity (10 copies/μL each) and specificity (100%) compared to traditional culture and sequencing methods. Furthermore, we applied this method to spiked clinical samples, 30 cerebrospinal fluids and 30 bronchoalveolar lavage fluids, which kept good detection performance. This novel rapid duplex flap probe-based isothermal assay is a promising and robust tool for applications in differential diagnosis of the Cryptococcus neoformans and Cryptococcus gattii in clinical settings, especially when clinical suspicion for cryptococcal disease is high and epidemiological studies.</p

Parallel-META 2.0: Enhanced Metagenomic Data Analysis with Functional Annotation, High Performance Computing and Advanced Visualization

<div><p>The metagenomic method directly sequences and analyses genome information from microbial communities. The main computational tasks for metagenomic analyses include taxonomical and functional structure analysis for all genomes in a microbial community (also referred to as a metagenomic sample). With the advancement of Next Generation Sequencing (NGS) techniques, the number of metagenomic samples and the data size for each sample are increasing rapidly. Current metagenomic analysis is both data- and computation- intensive, especially when there are many species in a metagenomic sample, and each has a large number of sequences. As such, metagenomic analyses require extensive computational power. The increasing analytical requirements further augment the challenges for computation analysis. In this work, we have proposed Parallel-META 2.0, a metagenomic analysis software package, to cope with such needs for efficient and fast analyses of taxonomical and functional structures for microbial communities. Parallel-META 2.0 is an extended and improved version of Parallel-META 1.0, which enhances the taxonomical analysis using multiple databases, improves computation efficiency by optimized parallel computing, and supports interactive visualization of results in multiple views. Furthermore, it enables functional analysis for metagenomic samples including short-reads assembly, gene prediction and functional annotation. Therefore, it could provide accurate taxonomical and functional analyses of the metagenomic samples in high-throughput manner and on large scale.</p></div

Information about multiple 16S rRNA reference databases.

<p>Information about multiple 16S rRNA reference databases.</p

Average error rate of taxonomical analysis of Parallel-META 2.0.

<p>Average error rate of taxonomical analysis of Parallel-META 2.0.</p

Statistical results of Parallel-META 2.0 functional analysis.

<p>Refer to <b>Table S3</b> and <b>Table S4</b> in <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089323#pone.0089323.s001" target="_blank">File S1</a></b> for details of results on these samples. Notice that as many of the speciesd in real samples do not have complete genome sequences, the expected number of genes that could be predicted is hard to estimate for these samples.</p

Information about simulated metagenomic datasets.

<p>Refer to <b>Table S1</b> (<b>A</b>)–(<b>J</b>) in <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089323#pone.0089323.s001" target="_blank">File S1</a></b> for detailed strains and their relative abundances for these simulated samples.</p

Running time of Parallel-META 1.0 and 2.0 with the same datasets and reference database (Greengenes).

<p>The Y-axis is in 10-based log scale.</p

Functional annotation results by SEED based method.

<p>Functional annotation results by SEED based method.</p

Functional annotation results by GO-term based method.

<p>Functional annotation results by GO-term based method.</p

The visualization effects for different kinds of results.

<p>(A) Global view, (B) Sample view, (C) Sub-sample view and (D) Phylogenetic view, (E) Sample view for SEED based functional analysis, and (F) GO-term based analysis.</p