Ping Hu

Bio: Ping Hu is an academic researcher from Nanjing Medical University. The author has contributed to research in topics: Prenatal diagnosis & Exome sequencing. The author has an hindex of 22, co-authored 77 publications receiving 10302 citations. Previous affiliations of Ping Hu include Energy Biosciences Institute & Lawrence Berkeley National Laboratory.

Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB

Abstract: A 16S rRNA gene database (http://greengenes.lbl.gov) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria.

Whole-Genome Transcriptional Analysis of Heavy Metal Stresses in Caulobacter crescentus

Abstract: The bacterium Caulobacter crescentus and related stalk bacterial species are known for their distinctive ability to live in low-nutrient environments, a characteristic of most heavy metal-contaminated sites. Caulobacter crescentus is a model organism for studying cell cycle regulation with well-developed genetics. We have identified the pathways responding to heavy-metal toxicity in C. crescentus to provide insights for the possible application of Caulobacter to environmental restoration. We exposed C. crescentus cells to four heavy metals (chromium, cadmium, selenium, and uranium) and analyzed genome-wide transcriptional activities postexposure using an Affymetrix GeneChip microarray. C. crescentus showed surprisingly high tolerance to uranium, a possible mechanism for which may be the formation of extracellular calcium-uranium-phosphate precipitates. The principal response to these metals was protection against oxidative stress (up-regulation of manganese-dependent superoxide dismutase sodA). Glutathione S-transferase, thioredoxin, glutaredoxins, and DNA repair enzymes responded most strongly to cadmium and chromate. The cadmium and chromium stress response also focused on reducing the intracellular metal concentration, with multiple efflux pumps employed to remove cadmium, while a sulfate transporter was down-regulated to reduce nonspecific uptake of chromium. Membrane proteins were also up-regulated in response to most of the metals tested. A two-component signal transduction system involved in the uranium response was identified. Several differentially regulated transcripts from regions previously not known to encode proteins were identified, demonstrating the advantage of evaluating the transcriptome by using whole-genome microarrays.

High-throughput identification of transcription start sites, conserved promoter motifs and predicted regulons

Abstract: Using 62 probe-level datasets obtained with a custom-designed Caulobacter crescentus microarray chip, we identify transcriptional start sites of 769 genes, 53 of which are transcribed from multiple start sites. Transcriptional start sites are identified by analyzing probe signal cross-correlation matrices created from probe pairs tiled every 5 bp upstream of the genes. Signals from probes binding the same message are correlated. The contribution of each promoter for genes transcribed from multiple promoters is identified. Knowing the transcription start site enables targeted searching for regulatory-protein binding motifs in the promoter regions of genes with similar expression patterns. We identified 27 motifs, 17 of which share no similarity to the characterized motifs of other C. crescentus transcriptional regulators. Using these motifs, we predict coregulated genes. We verified novel promoter motifs that regulate stress-response genes, including those responding to uranium challenge, a stress-response sigma factor and a stress-response noncoding RNA.

Genome-Resolved Metagenomic Analysis Reveals Roles for Candidate Phyla and Other Microbial Community Members in Biogeochemical Transformations in Oil Reservoirs

Abstract: Oil reservoirs are major sites of methane production and carbon turnover, processes with significant impacts on energy resources and global biogeochemical cycles. We applied a cultivation-independent genomic approach to define microbial community membership and predict roles for specific organisms in biogeochemical transformations in Alaska North Slope oil fields. Produced water samples were collected from six locations between 1,128 m (24 to 27°C) and 2,743 m (80 to 83°C) below the surface. Microbial community complexity decreased with increasing temperature, and the potential to degrade hydrocarbon compounds was most prevalent in the lower-temperature reservoirs. Sulfate availability, rather than sulfate reduction potential, seems to be the limiting factor for sulfide production in some of the reservoirs under investigation. Most microorganisms in the intermediate- and higher-temperature samples were related to previously studied methanogenic and nonmethanogenic archaea and thermophilic bacteria, but one candidate phylum bacterium, a member of the Acetothermia (OP1), was present in Kuparuk sample K3. The greatest numbers of candidate phyla were recovered from the mesothermic reservoir samples SB1 and SB2. We reconstructed a nearly complete genome for an organism from the candidate phylum Parcubacteria (OD1) that was abundant in sample SB1. Consistent with prior findings for members of this lineage, the OD1 genome is small, and metabolic predictions support an obligately anaerobic, fermentation-based lifestyle. At moderate abundance in samples SB1 and SB2 were members of bacteria from other candidate phyla, including Microgenomates (OP11), Atribacteria (OP9), candidate phyla TA06 and WS6, and Marinimicrobia (SAR406). The results presented here elucidate potential roles of organisms in oil reservoir biological processes. IMPORTANCE The activities of microorganisms in oil reservoirs impact petroleum resource quality and the global carbon cycle. We show that bacteria belonging to candidate phyla are present in some oil reservoirs and provide the first insights into their potential roles in biogeochemical processes based on several nearly complete genomes.

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

Abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

Abstract: mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.

UPARSE: highly accurate OTU sequences from microbial amplicon reads

Abstract: Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.

phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Abstract: Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

FastTree 2--approximately maximum-likelihood trees for large alignments.

Abstract: Background We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability.