Comparative Analysis and Data Provenance for 1,113 Bacterial Genome Assemblies

The quality and traceability of microbial genomics data in public databases is deteriorating as they rapidly expand and struggle to cope with data curation challenges. While the availability of public genomic data has become essential for modern life sciences research, the curation of the data is a growing area of concern that has significant real-world impacts on public health epidemiology, drug discovery, and environmental biosurveillance research. While public microbial genome databases such as NCBI's RefSeq database leverage the scalability of crowd sourcing for growth, they do not require data provenance to the original biological source materials or accurate descriptions of how the data was produced. Here, we describe the de novo assembly of 1,113 bacterial genome references produced from authenticated materials sourced from the American Type Culture Collection (ATCC), each with full data provenance. Over 98% of these ATCC Standard Reference Genomes (ASRGs) are superior to assemblies for comparable strains found in NCBI's RefSeq database. Comparative genomics analysis revealed significant issues in RefSeq bacterial genome assemblies related to genome completeness, mutations, structural differences, metadata errors, and gaps in traceability to the original biological source materials. For example, nearly half of RefSeq assemblies lack details on sample source information, sequencing technology, or bioinformatics methods. We suggest there is an intrinsic connection between the quality of genomic metadata, the traceability of the data, and the methods used to produce them with the quality of the resulting genome assemblies themselves. Our results highlight common problems with "reference genomes" and underscore the importance of data provenance for precision science and reproducibility. These gaps in metadata accuracy and data provenance represent an "elephant in the room" for microbial genomics research, but addressing these issues would require raising the level of accountability for data depositors and our own expectations of data quality.

Draft Genome Sequences of 10 Bacteria from the Marine Pseudoalteromonas Group

Here, we report the draft genome sequences of 10 marine Pseudoalteromonas bacteria which were isolated, assembled, and annotated by undergraduate students participating in a marine microbial genomics course. Genomic comparisons suggest that 7 of the 10 strains are novel isolates, providing a resource for future marine microbiology investigations.

Metagenomic Data Assembly – The Way of Decoding Unknown Microorganisms

Metagenomics is a segment of conventional microbial genomics dedicated to the sequencing and analysis of combined genomic DNA of entire environmental samples. The most critical step of the metagenomic data analysis is the reconstruction of individual genes and genomes of the microorganisms in the communities using metagenomic assemblers – computational programs that put together small fragments of sequenced DNA generated by sequencing instruments. Here, we describe the challenges of metagenomic assembly, a wide spectrum of applications in which metagenomic assemblies were used to better understand the ecology and evolution of microbial ecosystems, and present one of the most efficient microbial assemblers, SPAdes that was upgraded to become applicable for metagenomics.

The Next Million Names for Archaea and Bacteria

Latin binomials, popularised in the eighteenth century by the Swedish naturalist Linnaeus, have stood the test of time in providing a stable, clear and memorable system of nomenclature across biology. However, relentless and ever-deeper exploration and analysis of the microbial world has created an urgent unmet need for huge numbers of new names for Archaea and Bacteria. Manual creation of such names remains difficult and slow and typically relies on expert-driven nomenclatural quality control. Keen to ensure the legacy of Linnaeus lives on in the age of microbial genomics and metagenomics, we propose an automated approach, employing combinatorial concatenation of roots from Latin and Greek to create linguistically correct names for genera and species that can be used off the shelf as needed. As proof of principle, we document over a million new names for Bacteria and Archaea. We are confident that our approach provides a road map for how to create new names for decades to come.

M1CR0B1AL1Z3R—a user-friendly web server for the analysis of large-scale microbial genomics data

Large-scale mining and analysis of bacterial datasets contribute to the comprehensive characterization of complex microbial dynamics within a microbiome and among different bacterial strains, e.g., during disease outbreaks. The study of large-scale bacterial evolutionary dynamics poses many challenges. These include data-mining steps, such as gene annotation, ortholog detection, sequence alignment, and phylogeny reconstruction. These steps require the use of multiple bioinformatics tools and ad-hoc programming scripts, making the entire process cumbersome, tedious and error-prone due to manual handling. This motivated us to develop the M1CR0B1AL1Z3R web server, a ‘one-stop shop’ for conducting microbial genomics data analyses via a simple graphical user interface (Avram, et al., Nucleic Acids Res., 2019). Some of the features implemented in M1CR0B1AL1Z3R are: (i) extracting putative open reading frames and comparative genomics analysis of gene content; (ii) extracting orthologous sets and analyzing their size distribution; (iii) analyzing gene presence-absence patterns; (iv) reconstructing a phylogenetic tree based on the extracted orthologous set; (v) inferring GC-content variation among lineages. M1CR0B1AL1Z3R facilitates the mining and analysis of dozens of bacterial genomes using advanced techniques, with the click of a button. M1CR0B1AL1Z3R is freely available at https://microbializer.tau.ac.il/ [https://microbializer.tau.ac.il/].