Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters.

Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the predicted BGCs revealed large gene cluster families, the vast majority uncharacterized. We experimentally characterized the most prominent family, consisting of two subfamilies of hundreds of BGCs distributed throughout the Proteobacteria; their products are aryl polyenes, lipids with an aryl head group conjugated to a polyene tail. We identified a distant relationship to a third subfamily of aryl polyene BGCs, and together the three subfamilies represent the largest known family of biosynthetic gene clusters, with more than 1,000 members. Although these clusters are widely divergent in sequence, their small molecule products are remarkably conserved, indicating for the first time the important roles these compounds play in Gram-negative cell biology.

Maximum power transfer in a real metal slit: an analytic approach.

We present a fully analytic theory to study the power and field enhancement inside a real metal slit. A generalized formula for the reflection coefficient at the interface of the slit is derived. The resulting expression is purely analytic and the reflection coefficient can be simply evaluated to provide physical insight, while not requiring complicated numerical simulations. The calculated values of reflection phase and amplitude are then used in the Fabry-Pérot formalism to compute the electric field and the power inside the slit. It is shown that the power attains its maximum value when the scattering and the absorption cross-sections of the slit are equal, a confirmation of the maximum power transfer theorem for this case. The analytic results agree well with numerical simulations, which is promising for optimizing performance in applications ranging from modulators to optical tweezers.

An integrated workflow for phenazine-modifying enzyme characterization.

Increasing availability of new genomes and putative biosynthetic gene clusters (BGCs) has extended the opportunity to access novel chemical diversity for agriculture, medicine, environmental and industrial purposes. However, functional characterization of BGCs through heterologous expression is limited because expression may require complex regulatory mechanisms, specific folding or activation. We developed an integrated workflow for BGC characterization that integrates pathway identification, modular design, DNA synthesis, assembly and characterization. This workflow was applied to characterize multiple phenazine-modifying enzymes. Phenazine pathways are useful for this workflow because all phenazines are derived from a core scaffold for modification by diverse modifying enzymes (PhzM, PhzS, PhzH, and PhzO) that produce characterized compounds. We expressed refactored synthetic modules of previously uncharacterized phenazine BGCs heterologously in Escherichia coli and were able to identify metabolic intermediates they produced, including a previously unidentified metabolite. These results demonstrate how this approach can accelerate functional characterization of BGCs.

Microbial species delineation using whole genome sequences.

Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness. In this work, we demonstrate that the combination of gANI and the alignment fraction (AF) between two genomes accurately reflects their genomic relatedness. We introduce an efficient implementation of AF,gANI and discuss its successful application to 86.5M genome pairs between 13,151 prokaryotic genomes assigned to 3032 species. Subsequently, by comparing the genome clusters obtained from complete linkage clustering of these pairs to existing taxonomy, we observed that nearly 18% of all prokaryotic species suffer from anomalies in species definition. Our results can be used to explore central questions such as whether microorganisms form a continuum of genetic diversity or distinct species represented by distinct genetic signatures. We propose that this precise and objective AF,gANI-based species definition: the MiSI (Microbial Species Identifier) method, be used to address previous inconsistencies in species classification and as the primary guide for new taxonomic species assignment, supplemented by the traditional polyphasic approach, as required.

Metagenomic investigation of the geologically unique Hellenic Volcanic Arc reveals a distinctive ecosystem with unexpected physiology.

Hydrothermal vents represent a deep, hot, aphotic biosphere where chemosynthetic primary producers, fuelled by chemicals from Earth's subsurface, form the basis of life. In this study, we examined microbial mats from two distinct volcanic sites within the Hellenic Volcanic Arc (HVA). The HVA is geologically and ecologically unique, with reported emissions of CO2 -saturated fluids at temperatures up to 220°C and a notable absence of macrofauna. Metagenomic data reveals highly complex prokaryotic communities composed of chemolithoautotrophs, some methanotrophs, and to our surprise, heterotrophs capable of anaerobic degradation of aromatic hydrocarbons. Our data suggest that aromatic hydrocarbons may indeed be a significant source of carbon in these sites, and instigate additional research into the nature and origin of these compounds in the HVA. Novel physiology was assigned to several uncultured prokaryotic lineages; most notably, a SAR406 representative is attributed with a role in anaerobic hydrocarbon degradation. This dataset, the largest to date from submarine volcanic ecosystems, constitutes a significant resource of novel genes and pathways with potential biotechnological applications.

IMG 4 version of the integrated microbial genomes comparative analysis system.

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG's data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG's annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).

IMG/M 4 version of the integrated metagenome comparative analysis system.

IMG/M (http://img.jgi.doe.gov/m) provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in the context of a comprehensive set of reference genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG/M's data content and analytical tools have expanded continuously since its first version was released in 2007. Since the last report published in the 2012 NAR Database Issue, IMG/M's database architecture, annotation and data integration pipelines and analysis tools have been extended to copewith the rapid growth in the number and size of metagenome data sets handled by the system. IMG/M data marts provide support for the analysis of publicly available genomes, expert review of metagenome annotations (IMG/M ER: http://img.jgi.doe.gov/mer) and Human Microbiome Project (HMP)-specific metagenome samples (IMG/M HMP: http://img.jgi.doe.gov/imgm_hmp).

A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea.

Sequencing of bacterial and archaeal genomes has revolutionized our understanding of the many roles played by microorganisms. There are now nearly 1,000 completed bacterial and archaeal genomes available, most of which were chosen for sequencing on the basis of their physiology. As a result, the perspective provided by the currently available genomes is limited by a highly biased phylogenetic distribution. To explore the value added by choosing microbial genomes for sequencing on the basis of their evolutionary relationships, we have sequenced and analysed the genomes of 56 culturable species of Bacteria and Archaea selected to maximize phylogenetic coverage. Analysis of these genomes demonstrated pronounced benefits (compared to an equivalent set of genomes randomly selected from the existing database) in diverse areas including the reconstruction of phylogenetic history, the discovery of new protein families and biological properties, and the prediction of functions for known genes from other organisms. Our results strongly support the need for systematic 'phylogenomic' efforts to compile a phylogeny-driven 'Genomic Encyclopedia of Bacteria and Archaea' in order to derive maximum knowledge from existing microbial genome data as well as from genome sequences to come.

IMG/M: the integrated metagenome data management and comparative analysis system.

The integrated microbial genomes and metagenomes (IMG/M) system provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in a comprehensive integrated context. IMG/M integrates metagenome data sets with isolate microbial genomes from the IMG system. IMG/M's data content and analytical capabilities have been extended through regular updates since its first release in 2007. IMG/M is available at http://img.jgi.doe.gov/m. A companion IMG/M systems provide support for annotation and expert review of unpublished metagenomic data sets (IMG/M ER: http://img.jgi.doe.gov/mer).

GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes.

We present 'gene prediction improvement pipeline' (GenePRIMP; http://geneprimp.jgi-psf.org/), a computational process that performs evidence-based evaluation of gene models in prokaryotic genomes and reports anomalies including inconsistent start sites, missed genes and split genes. We found that manual curation of gene models using the anomaly reports generated by GenePRIMP improved their quality, and demonstrate the applicability of GenePRIMP in improving finishing quality and comparing different genome-sequencing and annotation technologies.

Tarlatamab, a First-in-Class DLL3-Targeted Bispecific T-Cell Engager, in Recurrent Small-Cell Lung Cancer: An Open-Label, Phase I Study.

PURPOSE: Small-cell lung cancer (SCLC) is an aggressive malignancy with limited treatments. Delta-like ligand 3 (DLL3) is aberrantly expressed in most SCLC. Tarlatamab (AMG 757), a bispecific T-cell engager molecule, binds both DLL3 and CD3 leading to T-cellb-mediated tumor lysis. Herein, we report phase I results of tarlatamab in patients with SCLC. PATIENTS AND METHODS: This study evaluated tarlatamab in patients with relapsed/refractory SCLC. The primary end point was safety. Secondary end points included antitumor activity by modified RECIST 1.1, overall survival, and pharmacokinetics. RESULTS: By July 19, 2022, 107 patients received tarlatamab in dose exploration (0.003 to 100 mg; n = 73) and expansion (100 mg; n = 34) cohorts. Median prior lines of anticancer therapy were 2 (range, 1-6); 49.5% received antiprogrammed death-1/programmed death ligand-1 therapy. Any-grade treatment-related adverse events occurred in 97 patients (90.7%) and grade b % 3 in 33 patients (30.8%). One patient (1%) had grade 5 pneumonitis. Cytokine release syndrome was the most common treatment-related adverse event, occurring in 56 patients (52%) including grade 3 in one patient (1%). Maximum tolerated dose was not reached. Objective response rate was 23.4% (95% CI, 15.7 to 32.5) including two complete and 23 partial responses. The median duration of response was 12.3 months (95% CI, 6.6 to 14.9). The disease control rate was 51.4% (95% CI, 41.5 to 61.2). The median progression-free survival and overall survival were 3.7 months (95% CI, 2.1 to 5.4) and 13.2 months (95% CI, 10.5 to not reached), respectively. Exploratory analysis suggests that selecting for increased DLL3 expression can result in increased clinical benefit. CONCLUSION: In patients with heavily pretreated SCLC, tarlatamab demonstrated manageable safety with encouraging response durability. Further evaluation of this promising molecule is ongoing.

High-quality draft genome sequence of the Opitutaceae bacterium strain TAV1, a symbiont of the wood-feeding termite Reticulitermes flavipes.

Microbial communities in the termite hindgut are essential for degrading plant material. We present the high-quality draft genome sequence of the Opitutaceae bacterium strain TAV1, the first member of the phylum Verrucomicrobia to be isolated from wood-feeding termites. The genomic analysis reveals genes coding for lignocellulosic degradation and nitrogen fixation.

Complete genome sequences of Desulfosporosinus orientis DSM765T, Desulfosporosinus youngiae DSM17734T, Desulfosporosinus meridiei DSM13257T, and Desulfosporosinus acidiphilus DSM22704T.

Desulfosporosinus species are sulfate-reducing bacteria belonging to the Firmicutes. Their genomes will give insights into the genetic repertoire and evolution of sulfate reducers typically thriving in terrestrial environments and able to degrade toluene (Desulfosporosinus youngiae), to reduce Fe(III) (Desulfosporosinus meridiei, Desulfosporosinus orientis), and to grow under acidic conditions (Desulfosporosinus acidiphilus).

The Genome of the Acid Soil-Adapted Strain Rhizobium favelukesii OR191 Encodes Determinants for Effective Symbiotic Interaction With Both an Inverted Repeat Lacking Clade and a Phaseoloid Legume Host.

Although Medicago sativa forms highly effective symbioses with the comparatively acid-sensitive genus Ensifer, its introduction into acid soils appears to have selected for symbiotic interactions with acid-tolerant R. favelukesii strains. Rhizobium favelukesii has the unusual ability of being able to nodulate and fix nitrogen, albeit sub-optimally, not only with M. sativa but also with the promiscuous host Phaseolus vulgaris. Here we describe the genome of R. favelukesii OR191 and genomic features important for the symbiotic interaction with both of these hosts. The OR191 draft genome contained acid adaptation loci, including the highly acid-inducible lpiA/acvB operon and olsC, required for production of lysine- and ornithine-containing membrane lipids, respectively. The olsC gene was also present in other acid-tolerant Rhizobium strains but absent from the more acid-sensitive Ensifer microsymbionts. The OR191 symbiotic genes were in general more closely related to those found in Medicago microsymbionts. OR191 contained the nodA, nodEF, nodHPQ, and nodL genes for synthesis of polyunsaturated, sulfated and acetylated Nod factors that are important for symbiosis with Medicago, but contained a truncated nodG, which may decrease nodulation efficiency with M. sativa. OR191 contained an E. meliloti type BacA, which has been shown to specifically protect Ensifer microsymbionts from Medicago nodule-specific cysteine-rich peptides. The nitrogen fixation genes nifQWZS were present in OR191 and P. vulgaris microsymbionts but absent from E. meliloti-Medicago microsymbionts. The ability of OR191 to nodulate and fix nitrogen symbiotically with P. vulgaris indicates that this host has less stringent requirements for nodulation than M. sativa but may need rhizobial strains that possess nifQWZS for N2-fixation to occur. OR191 possessed the exo genes required for the biosynthesis of succinoglycan, which is required for the Ensifer-Medicago symbiosis. However, 1H-NMR spectra revealed that, in the conditions tested, OR191 exopolysaccharide did not contain a succinyl substituent but instead contained a 3-hydroxybutyrate moiety, which may affect its symbiotic performance with Medicago hosts. These findings provide a foundation for the genetic basis of nodulation requirements and symbiotic effectiveness with different hosts.

Complete genome sequences for the anaerobic, extremely thermophilic plant biomass-degrading bacteria Caldicellulosiruptor hydrothermalis, Caldicellulosiruptor kristjanssonii, Caldicellulosiruptor kronotskyensis, Caldicellulosiruptor owensensis, and Caldicellulosiruptor lactoaceticus.

The genus Caldicellulosiruptor contains the most thermophilic, plant biomass-degrading bacteria isolated to date. Previously, genome sequences from three cellulolytic members of this genus were reported (C. saccharolyticus, C. bescii, and C. obsidiansis). To further explore the physiological and biochemical basis for polysaccharide degradation within this genus, five additional genomes were sequenced: C. hydrothermalis, C. kristjanssonii, C. kronotskyensis, C. lactoaceticus, and C. owensensis. Taken together, the seven completed and one draft-phase Caldicellulosiruptor genomes suggest that, while central metabolism is highly conserved, significant differences in glycoside hydrolase inventories and numbers of carbohydrate transporters exist, a finding which likely relates to variability observed in plant biomass degradation capacity.

Genome sequence of "Candidatus Frankia datiscae" Dg1, the uncultured microsymbiont from nitrogen-fixing root nodules of the dicot Datisca glomerata.

Members of the noncultured clade of Frankia enter into root nodule symbioses with actinorhizal species from the orders Cucurbitales and Rosales. We report the genome sequence of a member of this clade originally from Pakistan but obtained from root nodules of the American plant Datisca glomerata without isolation in culture.

Estimating DNA coverage and abundance in metagenomes using a gamma approximation.

MOTIVATION: Shotgun sequencing generates large numbers of short DNA reads from either an isolated organism or, in the case of metagenomics projects, from the aggregate genome of a microbial community. These reads are then assembled based on overlapping sequences into larger, contiguous sequences (contigs). The feasibility of assembly and the coverage achieved (reads per nucleotide or distinct sequence of nucleotides) depend on several factors: the number of reads sequenced, the read length and the relative abundances of their source genomes in the microbial community. A low coverage suggests that most of the genomic DNA in the sample has not been sequenced, but it is often difficult to estimate either the extent of the uncaptured diversity or the amount of additional sequencing that would be most efficacious. In this work, we regard a metagenome as a population of DNA fragments (bins), each of which may be covered by one or more reads. We employ a gamma distribution to model this bin population due to its flexibility and ease of use. When a gamma approximation can be found that adequately fits the data, we may estimate the number of bins that were not sequenced and that could potentially be revealed by additional sequencing. We evaluated the performance of this model using simulated metagenomes and demonstrate its applicability on three recent metagenomic datasets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic potential of Marinobacter aquaeolei, a biogeochemical "opportunitroph".

The genus of Marinobacter is one of the most ubiquitous in the global oceans and assumed to significantly impact various biogeochemical cycles. The genome structure and content of Marinobacter aquaeolei VT8 was analyzed and compared with those from other organisms with diverse adaptive strategies. Here, we report the many "opportunitrophic" genetic characteristics and strategies that M. aquaeolei has adopted to promote survival under various environmental conditions. Genome analysis revealed its metabolic potential to utilize oxygen and nitrate as terminal electron acceptors, iron as an electron donor, and urea, phosphonate, and various hydrocarbons as alternative N, P, and C sources, respectively. Miscellaneous sensory and defense mechanisms, apparently acquired via horizontal gene transfer, are involved in the perception of environmental fluctuations and antibiotic, phage, toxin, and heavy metal resistance, enabling survival under adverse conditions, such as oil-polluted water. Multiple putative integrases, transposases, and plasmids appear to have introduced additional metabolic potential, such as phosphonate degradation. The genomic potential of M. aquaeolei and its similarity to other opportunitrophs are consistent with its cosmopolitan occurrence in diverse environments and highly variable lifestyles.

Integration of phenotypic metadata and protein similarity in Archaea using a spectral bipartitioning approach.

In order to simplify and meaningfully categorize large sets of protein sequence data, it is commonplace to cluster proteins based on the similarity of those sequences. However, it quickly becomes clear that the sequence flexibility allowed a given protein varies significantly among different protein families. The degree to which sequences are conserved not only differs for each protein family, but also is affected by the phylogenetic divergence of the source organisms. Clustering techniques that use similarity thresholds for protein families do not always allow for these variations and thus cannot be confidently used for applications such as automated annotation and phylogenetic profiling. In this work, we applied a spectral bipartitioning technique to all proteins from 53 archaeal genomes. Comparisons between different taxonomic levels allowed us to study the effects of phylogenetic distances on cluster structure. Likewise, by associating functional annotations and phenotypic metadata with each protein, we could compare our protein similarity clusters with both protein function and associated phenotype. Our clusters can be analyzed graphically and interactively online.