M. B. Scholz

Next generation sequencing and bioinformatic bottlenecks: the current state of metagenomic data analysis

The recent technological advances in next generation sequencing have brought the field closer to the goal of reconstructing all genomes within a community by presenting high throughput sequencing at much lower costs. While these next-generation sequencing technologies have allowed a massive increase in available raw sequence data, there are a number of new informatics challenges and difficulties that must be addressed to improve the current state, and fulfill the promise of, metagenomics.

A novel metatranscriptomic approach to identify gene expression dynamics during extracellular electron transfer

Microbial respiration via extracellular electron transfer (EET) is a ubiquitous reaction that occurs throughout anoxic environments and is a driving force behind global biogeochemical cycling of metals. Here we identify specific EET-active microbes and genes in a diverse biofilm using an innovative approach to analyse the dynamic community-wide response to changing EET rates. We find that the most significant gene expression responses to applied EET stimuli occur in only two microbial groups, Desulfobulbaceae and Desulfuromonadales. Metagenomic analyses reveal high coverage draft genomes of these abundant and active microbes. Our metatranscriptomic results show known and unknown genes that are highly responsive to EET stimuli and associated with our identified draft genomes. This new approach yields a comprehensive image of functional microbes and genes related to EET activity in a diverse community, representing the next step towards unravelling complex microbial roles within a community and how microbes adapt to specific environmental stimuli.

Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools.

Draft Genome Sequence of Methylomicrobium buryatense Strain 5G, a Haloalkaline-Tolerant Methanotrophic Bacterium

ABSTRACT Robust growth of the gammaproteobacterium Methylomicrobium buryatense strain 5G on methane makes it an attractive system for CH4-based biocatalysis. Here we present a draft genome sequence of the strain that will provide a valuable framework for metabolic engineering of the core pathways for the production of valuable chemicals from methane.

Improved assemblies using a source-agnostic pipeline for MetaGenomic Assembly by Merging (MeGAMerge) of contigs

Assembly of metagenomic samples is a very complex process, with algorithms designed to address sequencing platform-specific issues, (read length, data volume, and/or community complexity), while also faced with genomes that differ greatly in nucleotide compositional biases and in abundance. To address these issues, we have developed a post-assembly process: MetaGenomic Assembly by Merging (MeGAMerge). We compare this process to the performance of several assemblers, using both real, and in-silico generated samples of different community composition and complexity. MeGAMerge consistently outperforms individual assembly methods, producing larger contigs with an increased number of predicted genes, without replication of data. MeGAMerge contigs are supported by read mapping and contig alignment data, when using synthetically-derived and real metagenomic data, as well as by gene prediction analyses and similarity searches. MeGAMerge is a flexible method that generates improved metagenome assemblies, with the ability to accommodate upcoming sequencing platforms, as well as present and future assembly algorithms.

Draft Genome Assembly of Acinetobacter baumannii ATCC 19606

ABSTRACT Acinetobacter baumannii is an emerging nosocomial pathogen, and therefore high-quality genome assemblies for this organism are needed to aid in detection, diagnostic, and treatment technologies. Here we present the improved draft assembly of A. baumannii ATCC 19606 in two scaffolds. This 3,953,621-bp genome contains 3,750 coding regions and has a 39.1% G+C content.

Whole-Genome Assemblies of 56 Burkholderia Species

ABSTRACT Burkholderia is a genus of betaproteobacteria that includes three notable human pathogens: B. cepacia, B. pseudomallei, and B. mallei. While B. pseudomallei and B. mallei are considered potential biowarfare agents, B. cepacia infections are largely limited to cystic fibrosis patients. Here, we present 56 Burkholderia genomes from 8 distinct species.

Complete Genome Sequence of Stenotrophomonas maltophilia Type Strain 810-2 (ATCC 13637).

ABSTRACT An emerging nosocomial pathogen, Stenotrophomonas maltophila has a high mortality rate in those it infects. Here, we present the complete genome sequence of Stenotrophomonas maltophilia 810-2 (ATCC 13637), the type strain of the species. The 5-Mb (66.1% G+C content) genome has been deposited in NCBI under accession number CP008838.

Whole-Genome Sequences of 24 Brucella Strains

ABSTRACT Brucella species are intracellular zoonotic pathogens which cause, among other pathologies, increased rates of abortion in ruminants. Human infections are generally associated with exposure to contaminated and unpasteurized dairy products; however Brucellae have been developed as bioweapons. Here we present 17 complete and 7 scaffolded genome assemblies of Brucella strains.

Complete Genome Sequence of Type Strain Pasteurella multocida subsp. multocida ATCC 43137.

ABSTRACT Soft-tissue infection by Pasteurella multocida in humans is usually associated with a dog- or cat-related injury, and these infections can become aggressive. We sequenced the type strain P. multocida subsp. multocida ATCC 43137 into a single closed chromosome consisting of 2,271,840 bp (40.4% G+C content), which is currently available in the NCBI GenBank under the accession number CP008918.