Tackling Hypotheticals in Helminth Genomes

Advancements in genome sequencing have led to the rapid accumulation of uncharacterized 'hypothetical proteins' in the public databases. Here we provide a community perspective and some best-practice approaches for the accurate functional annotation of uncharacterized genomic sequences.

Identification and prioritization of macrolideresistance genes with hypothetical annotation inStreptococcus pneumoniae

Macrolide resistant Streptococcus pneumoniae infections have limited treatment options. While some resistance mechanisms are well established, ample understanding is limited by incomplete genome annotation (hypothetical genes). Some hypothetical genes encode a domain of unknown function (DUF), a conserved protein domain with uncharacterized function. Here, we identify and confirm macrolide resistance genes. We further explore DUFs from macrolide resistance hypothetical genes to prioritize them for experimental characterization. We found gene similarities between two macrolide resistance gene signatures from untreated and either erythromycin- or spiramycin-treated resistant Streptococcus pneumoniae. We confirmed the association of these gene sets with macrolide resistance through comparison to gene signatures from (i) second erythromycin resistant Streptococcus pneumoniae strain, and (ii) erythromycin-treated sensitive Streptococcus pneumoniae strain, both from non-overlapping datasets. Examination into which cellular processes these macrolide resistance genes belong found connections to known resistance mechanisms such as increased amino acid biosynthesis and efflux genes, and decreased ribonucleotide biosynthesis genes, highlighting the predictive ability of the method used. 22 genes had hypothetical annotation with 10 DUFs associated with macrolide resistance. DUF characterization could uncover novel co-therapies that restore macrolide efficacy across multiple macrolide resistant species. Application of the methods to other antibiotic resistances could revolutionize treatment of resistant infections

A new drug design strategy: Killing drug resistant bacteria by deactivating their hypothetical genes

Despite that a bacterial genome is complicated by large numbers of horizontally transferred (HT) genes and function unknown hypothetical (FUN) genes, the Genic-Transcriptional-Stop-Signals-Ratio (TSSR) of a genome shows that HT and FUN genes are complementary to all other genes in the genome. When HT or certain FUN genes are omitted from the Escherichia coli K-12 genome, its Genomic-TSSR value becomes totally incomparable to other E. coli strains. The Genic-TSSR correlation tree of a pathogen shows that some FUN genes would form a unique cluster. Removing these genes by site-specific mutation or gene-knockout should lead to the demise of this pathogen.

Beyond Meta-Omics: Functional Genomics in Future Marine Microbiome Research

When President Bill Clinton and Francis Collins, then the director of the National Human Genome Research Institute, celebrated the near completion of the human genome sequence at the White House in the summer of 2000, it is unlikely that they or anyone else could have predicted the blossoming of meta-omics in the following two decades and their applications in modern human microbiome and environmental microbiome research. This transformation was enabled by the development of high-throughput sequencing technologies and sophisticated computational biology tools and bioinformatics software packages. Today, environmental meta-omics has undoubtedly revolutionized our understanding of ocean ecosystems, providing the genetic blueprint of oceanic microscopic organisms. In this review, I discuss the importance of functional genomics in future marine microbiome research and advocate a position for a gene-centric, bottom-up approach in modern oceanography. I propose that a synthesis of multidimensional approaches is required for a better understanding of the true functionality of the marine microbiome.