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At least 19 records

Codon bias, nucleotide selection, and genome size predict in situ bacterial growth rate and transcription in rewetted soil

In soils, the first rain after a prolonged dry period represents a major pulse event impacting soil microbial community function, yet we lack a full understanding of the genomic traits associated with the microbial response to rewetting. Genomic traits such as codon usage bias and genome size have been linked to bacterial growth in soils—however, often through measurements in culture. Here, we used metagenome-assembled genomes (MAGs) with 18 O-water stable isotope probing and metatranscriptomics to track genomic traits associated with growth and transcription of soil microorganisms over one week following rewetting of a grassland soil. We found that codon bias in ribosomal protein genes was the strongest predictor of growth rate. We also found higher growth rates in bacteria with smaller genomes, suggesting that reduced genome size enables a faster response to pulses in soil bacteria. Faster transcriptional upregulation of ribosomal protein genes was associated with high codon bias and increased nucleotide skew. We found that several of these relationships existed within phyla, indicating that these associations between genomic traits and activity could be generalized characteristics of soil bacteria. Finally, we used publicly available metagenomes to assess the distribution of codon bias across a pH gradient and found that microbial communities in higher pH soils—which are often more water limited and pulse driven—have higher codon usage bias in their ribosomal protein genes. Together, these results provide evidence that genomic characteristics affect soil microbial activity during rewetting and pose a potential fitness advantage for soil bacteria where water and nutrient availability are episodic.

59 BASIC BIOLOGICAL SCIENCES↗

The Western Lake Erie culture collection: A promising resource for evaluating the physiological and genetic diversity of Microcystis and its associated microbiome

Cyanobacterial harmful algal blooms (cyanoHABs) dominated by Microcystis spp. have significant public health and economic implications in freshwater bodies around the world. These blooms are capable of producing a variety of cyanotoxins, including microcystins, that affect fishing and tourism industries, human and environmental health, and access to drinking water. In this study, we isolated and sequenced the genomes of 21 primarily unialgal Microcystis cultures collected from western Lake Erie between 2017 and 2019. While some cultures isolated in different years have a high degree of genetic similarity (genomic Average Nucleotide Identity >99%), genomic data show that these cultures also represent much of the breadth of known Microcystis diversity in natural populations. Only five isolates contained all the genes required for microcystin biosynthesis while two isolates contained a previously described partial mcy operon. Microcystin production within cultures was also assessed using Enzyme-Linked Immunosorbent Assay (ELISA) and supported genomic results with high concentrations (up to 900 μg L⁻¹) in cultures with complete mcy operons and no or low toxin detected otherwise. These xenic cultures also contained a substantial diversity of bacteria associated with Microcystis, which has become increasingly recognized as an essential component of cyanoHAB community dynamics. These results highlight the genomic diversity among Microcystis strains and associated bacteria in Lake Erie, and their potential impacts on bloom development, toxin production, and toxin degradation. Furthermore, this culture collection significantly increases the availability of environmentally relevant Microcystis strains from temperate North America.

CyanoHABs↗

Rapid identification of enteric bacteria from whole genome sequences using average nucleotide identity metrics

Identification of enteric bacteria species by whole genome sequence (WGS) analysis requires a rapid and an easily standardized approach. We leveraged the principles of average nucleotide identity using MUMmer (ANIm) software, which calculates the percent bases aligned between two bacterial genomes and their corresponding ANI values, to set threshold values for determining species consistent with the conventional identification methods of known species. The performance of species identification was evaluated using two datasets: the Reference Genome Dataset v2 (RGDv2), consisting of 43 enteric genome assemblies representing 32 species, and the Test Genome Dataset (TGDv1), comprising 454 genome assemblies which is designed to represent all species needed to query for identification, as well as rare and closely related species. The RGDv2 contains six Campylobacter spp., three Escherichia/Shigella spp., one Grimontia hollisae, six Listeria spp., one Photobacterium damselae, two Salmonella spp., and thirteen Vibrio spp., while the TGDv1 contains 454 enteric bacterial genomes representing 42 different species. The analysis showed that, when a standard minimum of 70% genome bases alignment existed, the ANI threshold values determined for these species were ≥95 for Escherichia/Shigella and Vibrio species, ≥93% for Salmonella species, and ≥92% for Campylobacter and Listeria species. Using these metrics, the RGDv2 accurately classified all validation strains in TGDv1 at the species level, which is consistent with the classification based on previous gold standard methods.

59 BASIC BIOLOGICAL SCIENCES↗

Paraburkholderia madseniana sp. nov., a phenolic acid-degrading bacterium isolated from acidic forest soil

RP11 T was isolated from forest soil following enrichment with 4-hydroxybenzoic acid. Cells of RP11 T are aerobic, non-sporulating, exhibit swimming motility, and are rods (0.8 µm by 1.4 µm) that often occur as diplobacillus or in short chains (3–4 cells). Optimal growth on minimal media containing 4-hydroxybenzoic acid (µ=0.216 hr -1 ) occurred at 30 °C, pH 6.5 or 7.0 and 0% salinity. Comparative chemotaxonomic, genomic and phylogenetic analyses revealed the isolate was distinct from its closest relative type strains identified as Paraburkholderia aspalathi LMG 27731 T , Paraburkholderia fungorum LMG 16225 T and Paraburkholderia caffeinilytica CF1 T . Strain RP11 T is genetically distinct from P. aspalathi , its closest relative, in terms of 16S rRNA gene sequence similarity (98.7%), genomic average nucleotide identity (94%) and in silico DNA–DNA hybridization (56.7%±2.8). The composition of fatty acids and substrate utilization pattern differentiated strain RP11 T from its closest relatives, including growth on phthalic acid. Strain RP11 T encoded the greatest number of aromatic degradation genes of all eleven closely related type strains and uniquely encoded a phthalic acid dioxygenase and paralog of the 3-hydroxybenzoate 4-monooxygenase. The only ubiquinone detected in strain RP11 T was Q-8, and the major cellular fatty acids were C 16:0 , 3OH-C 16:0 , C 17:0 cyclo, C 19:0 cyclo ω8c, and summed feature 8 (C 18:1 ω7c/ω6c). On the basis of this polyphasic approach, it was determined that strain RP11 T represents a novel species from the genus Paraburkholderia for which the name Paraburkholderia madseniana sp. nov. is proposed. The type strain is RP11 T (=DSM 110123 T =LMG 31517 T ).

Microbiology↗

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates

ABSTRACT: Variation in the genome of Pseudomonas aeruginosa , an important pathogen, can have dramatic impacts on the bacterium’s ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based on their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical P. aeruginosa isolates using genomic information and corresponding virulence phenotypes in a mouse model of bacteremia. We defined the accessory genome of these isolates through the presence or absence of accessory genomic elements (AGEs), sequences present in some strains but not others. Machine learning models trained using AGEs were predictive of virulence, with a mean nested cross-validation accuracy of 75% using the random forest algorithm. However, individual AGEs did not have a large influence on the algorithm’s performance, suggesting instead that virulence predictions are derived from a diffuse genomic signature. These results were validated with an independent test set of 25 P. aeruginosa isolates whose virulence was predicted with 72% accuracy. Machine learning models trained using core genome single-nucleotide variants and whole-genome k-mers also predicted virulence. Our findings are a proof of concept for the use of bacterial genomes to predict pathogenicity in P. aeruginosa and highlight the potential of this approach for predicting patient outcomes. IMPORTANCE Pseudomonas aeruginosa is a clinically important Gram-negative opportunistic pathogen. P. aeruginosa shows a large degree of genomic heterogeneity both through variation in sequences found throughout the species (core genome) and through the presence or absence of sequences in different isolates (accessory genome). P. aeruginosa isolates also differ markedly in their ability to cause disease. In this study, we used machine learning to predict the virulence level of P. aeruginosa isolates in a mouse bacteremia model based on genomic content. We show that both the accessory and core genomes are predictive of virulence. This study provides a machine learning framework to investigate relationships between bacterial genomes and complex phenotypes such as virulence.

59 BASIC BIOLOGICAL SCIENCES↗

Nickase fidelity drives EvolvR-mediated diversification in mammalian cells

Abstract In vivo genetic diversifiers have previously enabled efficient searches of genetic variant fitness landscapes for continuous directed evolution. However, existing genomic diversification modalities for mammalian genomic loci exclusively rely on deaminases to generate transition mutations within target loci, forfeiting access to most missense mutations. Here, we engineer CRISPR-guided error-prone DNA polymerases (EvolvR) to diversify all four nucleotides within genomic loci in mammalian cells. We demonstrate that EvolvR generates both transition and transversion mutations throughout a mutation window of at least 40 bp and implement EvolvR to evolve previously unreported drug-resistantMAP2K1variants via substitutions not achievable with deaminases. Moreover, we discover that the nickase’s mismatch tolerance limits EvolvR’s mutation window and substitution biases in a gRNA-specific fashion. To compensate for gRNA-to-gRNA variability in mutagenesis, we maximize the number of gRNA target sequences by incorporating a PAM-flexible nickase into EvolvR. Finally, we find a strong correlation between predicted free energy changes underlying R-loop formation and EvolvR’s performance using a given gRNA. The EvolvR system diversifies all four nucleotides to enable the evolution of mammalian cells, while nuclease and gRNA-specific properties underlying nickase fidelity can be engineered to further enhance EvolvR’s mutation rates.

Science & Technology - Other Topics↗

Diversity of Sordariales Fungi: Identification of Seven New Species of Naviculisporaceae Through Morphological Analyses and Genome Sequencing

Thanks to next-generation sequencing (NGS) technologies, the diversity of fungi can now be investigated through the analysis of their genome sequences. Naviculisporaceae is a family within the Sordariales, whose diversity is not well-known, with only one genome sequence published for this family. Here, we report on the isolation and cultivation of 20 new strains of Naviculisporaceae. Their genome sequences, as well as those of the five commercially available strains, were determined, thus providing complete genome sequences for 25 new Naviculisporaceae strains. Species delimitation was conducted using a combination of (1) ITS + LSU phylogenetic analysis of the new isolates along with other known species of the family, (2) comparisons between DNA barcode sequences of the new strains with those of the known species, and (3) average genome-wide nucleotide identity calculation. We built a phylogenomic tree and studied the organization of the mating-type locus. In vitro fruiting was obtained for 16 strains, enabling the definition of seven new species, namely Pseudorhypophila gallica, Pseudorhypophila guyanensis Rhypophila alpibus, Rhypophila brasiliensis, Rhypophila camarguensis, Rhypophila reunionensis and Rhypophila thailandica, as well as two new combinations, namely Pseudorhypophila latipes and Pseudorhypophila oryzae. Eight strains for which in vitro fruiting was not obtained may belong to additional new species. These results expand the known diversity of the Naviculisporaceae and greatly enlarge the genomic data available for the family.

Naviculisporaceae↗

Monitoring Astronaut Health with DNA Sequencing

In recent years microbe a plethora of microbe populations have been identified onboard the ISS (International Space Station). Approaches for real-time tracking of microbes for routine housekeeping and food/water safety monitoring will be critical for mission safety and crew health on future longer duration missions to the Moon or Mars. This work is a proof-of-concept study demonstrating an end-to-end phylogenetic identification and full genome sequencing effort of multiple microbial populations. Our methodology utilized the ISS flight-certified WetLab-2 molecular toolbox and the Biomolecule Sequencer projects for real-time end-to-end on-orbit microbial biological samples processing and molecular analysis with real time results generated utilizing only field "offline" analytic software. For this experiment we colony-cultured several ISS isolated microorganisms before generation of the pre-sequencing library via the automated VolTRAX device which enabled high library turnover with little wet-bench activity or potential future costly astronaut time. The pre-sequencing library is diluted in loading buffer and injected into the MinION sample port, drawn into the nanopore window by capillary action, and sequenced using the MinKnown. 16S and full genome alignment, nucleotide matching, gene identification, and phylogenetic sorting was accomplished utilizing the Epi2me software and the offline NCBI Blast viral, microbiome, and human somatic databases. In short, the methodologies developed herein replace the myriad of specific, often highly targeted microbiological tests used in the clinical laboratory, which would be difficult if not impossible to currently implement aboard the ISS or in deep space, with a single metagenomics test.

genomics↗

Tandem repeats in giant archaeal Borg elements undergo rapid evolution and create new intrinsically disordered regions in proteins

Borgs are huge, linear extrachromosomal elements associated with anaerobic methane-oxidizing archaea. Striking features of Borg genomes are pervasive tandem direct repeat (TR) regions. Here, we present six new Borg genomes and investigate the characteristics of TRs in all ten complete Borg genomes. We find that TR regions are rapidly evolving, recently formed, arise independently, and are virtually absent in host Methanoperedens genomes. Flanking partial repeats and A-enriched character constrain the TR formation mechanism. TRs can be in intergenic regions, where they might serve as regulatory RNAs, or in open reading frames (ORFs). TRs in ORFs are under very strong selective pressure, leading to perfect amino acid TRs (aaTRs) that are commonly intrinsically disordered regions. Proteins with aaTRs are often extracellular or membrane proteins, and functionally similar or homologous proteins often have aaTRs composed of the same amino acids. We propose that Borg aaTR-proteins functionally diversify Methanoperedens and all TRs are crucial for specific Borg–host associations and possibly cospeciation.

59 BASIC BIOLOGICAL SCIENCES↗

Ancient polymorphisms contribute to genome-wide variation by long-term balancing selection and divergent sorting in Boechera stricta

Genomic variation is widespread, and both neutral and selective processes can generate similar patterns in the genome. These processes are not mutually exclusive, so it is difficult to infer the evolutionary mechanisms that govern population and species divergence. Boechera stricta is a perennial relative of Arabidopsis thaliana native to largely undisturbed habitats with two geographic and ecologically divergent subspecies. Here, we delineate the evolutionary processes driving the genetic diversity and population differentiation in this species. Using whole-genome re-sequencing data from 517 B. stricta accessions, we identify four genetic groups that diverged around 30-180 thousand years ago, with long-term small effective population sizes and recent population expansion after the Last Glacial Maximum. We find three genomic regions with elevated nucleotide diversity, totaling about 10% of the genome. These three regions of elevated nucleotide diversity show excess of intermediate-frequency alleles, higher absolute divergence ( d XY ), and lower relative divergence ( F ST ) than genomic background, and significant enrichment in immune-related genes, reflecting long-term balancing selection. Scattered across the genome, we also find regions with both high F ST and d XY among the groups, termed F ST -islands. Population genetic signatures indicate that F ST -islands with elevated divergence, which have experienced directional selection, are derived from divergent sorting of ancient polymorphisms. Our results suggest that long-term balancing selection on disease resistance genes may have maintained ancestral haplotypes across different geographical lineages, and unequal sorting of balanced polymorphisms may have generated genomic regions with elevated divergence. This study highlights the importance of ancestral balanced polymorphisms as crucial components of genome-wide variation.

59 BASIC BIOLOGICAL SCIENCES↗

Single-Cell Genomics of Novel Actinobacteria With the Wood–Ljungdahl Pathway Discovered in a Serpentinizing System

Serpentinite-hosted systems represent modern-day analogs of early Earth environments. In these systems, water-rock interactions generate highly alkaline and reducing fluids that can contain hydrogen, methane, and low-molecular-weight hydrocarbons-potent reductants capable of fueling microbial metabolism. In this study, we investigated the microbiota of Hakuba Happo hot springs (~50°C; pH~10.5–11), located in Nagano (Japan), which are impacted by the serpentinization process. Analysis of the 16S rRNA gene amplicon sequences revealed that the bacterial community comprises Nitrospirae (47%), “Parcubacteria” (19%), Deinococcus-Thermus (16%), and Actinobacteria (9%), among others. Notably, only 57 amplicon sequence variants (ASV) were detected, and fifteen of these accounted for 90% of the amplicons. Among the abundant ASVs, an early-branching, uncultivated actinobacterial clade identified as RBG-16-55-12 in the SILVA database was detected. Ten single-cell genomes (average pairwise nucleotide identity: 0.98–1.00; estimated completeness: 33–93%; estimated genome size: ~2.3 Mb) that affiliated with this clade were obtained. Taxonomic classification using single copy genes indicates that the genomes belong to the actinobacterial class-level clade UBA1414 in the Genome Taxonomy Database. Based on metabolic pathway predictions, these actinobacteria are anaerobes, capable of glycolysis, dissimilatory nitrate reduction and CO 2 fixation via the Wood–Ljungdahl (WL) pathway. Several other genomes within UBA1414 and two related class-level clades also encode the WL pathway, which has not yet been reported for the Actinobacteria phylum. For the Hakuba actinobacterium, the energy metabolism related to the WL pathway is likely supported by a combination of the Rnf complex, group 3b and 3d [NiFe]-hydrogenases, [FeFe]-hydrogenases, and V-type (H + /Na + pump) ATPase. The genomes also harbor a form IV ribulose 1,5-bisphosphate carboxylase/oxygenase (RubisCO) complex, also known as a RubisCO-like protein, and contain signatures of interactions with viruses, including clustered regularly interspaced short palindromic repeat (CRISPR) regions and several phage integrases. This is the first report and detailed genome analysis of a bacterium within the Actinobacteria phylum capable of utilizing the WL pathway. The Hakuba actinobacterium is a member of the clade UBA1414/RBG-16-55-12, formerly within the group “OPB41.” We propose to name this bacterium ‘Candidatus Hakubanella thermoalkaliphilus.'

59 BASIC BIOLOGICAL SCIENCES↗

Genomic prediction of hybrid performance for agronomic traits in sorghum

Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic-nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time-consuming, genomic prediction of parental lines and hybrids is based on genetic data genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency > 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76–0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12–90%, with plant height showing the greatest decline. Mean accuracies for predicting the general combining ability of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.

60 APPLIED LIFE SCIENCES↗

Edaphic controls on genome size and GC content of bacteria in soil microbial communities

Nutrient limitation has been shown to reduce bacterial genome size and influence nucleotide composition; however, much of this work has been conducted in marine systems and the factors which shape soil bacterial genomic traits remain largely unknown. Here, for this work, we determined average genome size, GC content, codon usage, and amino acid content from 398 soil metagenomes across a broad geographic range and used machine-learning to determine the environmental parameters that most strongly explain the distribution of these traits. We found that genomic trait averages were most related to pH, which we suggest is primarily due to the correlation of pH with several environmental parameters, particularly soil carbon content. Low pH soils had higher carbon to nitrogen ratios (C:N) and tended to have communities with lower GC content and larger genomes, potentially a response to increased physiological stress and a requirement for metabolic diversity. Conversely, communities in high pH and low soil C:N had smaller genomes and higher GC content—indicating potential resource driven selection against AT base pairs, which have a higher C:N than GC base pairs. Similarly, we found that nutrient conservation also applied to amino acid stoichiometry, where bacteria in soils with low C:N ratios tended to code for amino acids with lower C:N. Together, these relationships point towards fundamental mechanisms that underpin genome size, and nucleotide and amino acid selection in soil bacteria.

54 ENVIRONMENTAL SCIENCES↗

Thousands of small, novel genes predicted in global phage genomes

Small genes (<150nucleotides) have been systematically overlooked in phage genomes. We employ a large scale comparative genomics approach to predict >40,000 small-gene families in 2.3 million phage genome contigs. We find that small genes in phage genomes are approximately 3-fold more prevalent than in host prokaryotic genomes. Our approach enriches for small genes that are translated in microbiomes, suggesting the small genes identified are coding. More than 9,000 families encode potentially secreted or transmembrane proteins, more than 5,000families encode predicted anti-CRISPR proteins, and more than500families encode predicted antimicrobial proteins. By combining homology and genomic-neighborhood analyses, we reveal substantial novelty and diversity within phage biology, including small phage genes found in multiple host phyla, small genes encoding proteins that play essential roles in host infection, and small genes that share genomic neighborhoods and whose encoded proteins may share related functions.

Fremin, Brayon↗

DRAM example narrative

DRAM example narrative DRAM on KBase let's anyone run annotations using DRAM in the cloud. DRAM is an annotation tool that can annotate bacterial, archaeal and viral genomes and distills those annotatios into represetations of the functional genomic potential of those organisms. If you want to read more about DRAM you can check out the GitHub, wiki and journal article. DRAM annotate assemblies In KBase Assembly objects contain nucleotide sequences from genomes or metagenomes. DRAM can predict genes and annotate their function from KBase Assembly objects which may be microbial isolate genomes, metagenome assembled genomes or metagenomes. This is done with the Annotate and Distill Assemblies with DRAM app. This app can also anntoate AssemblySet objects which contain collection of Assembly objects. It also generates a Genome object and a GenomeSet object which can be used for further analysis with other KBase apps. The full annotations and other DRAM files are also available for download in the app.

59 BASIC BIOLOGICAL SCIENCES↗

Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees

There is overwhelming evidence that forest trees are locally adapted to climate. Thus, genecological models based on population phenotypes have been used to measure local adaptation, infer genetic maladaptation to climate, and guide assisted migration. However, instead of phenotypes, there is increasing interest in using genomic data for gene resource management. We used whole-genome resequencing and common-garden experiments to understand the genetic architecture of adaptive traits in black cottonwood. We studied the potential of using genome-wide association studies (GWAS) and genomic prediction to detect causal loci, identify climate-adapted phenotypes, and inform gene resource management. We analyzed population structure by partitioning phenotypic and genomic (single-nucleotide polymorphism) variation among 840 genotypes collected from 91 stands along 16 rivers. Most phenotypic variation (60 to 81%) occurred among populations and was strongly associated with climate. Population phenotypes were predicted well using genomic data (e.g., predictive abilityr> 0.9) but almost as well using climate or geography (r> 0.8). In contrast, genomic prediction within populations was poor (r< 0.2). We identified many GWAS associations among populations, but most appeared to be spurious based on pooled within-population analyses. Hierarchical partitioning of linkage disequilibrium and haplotype sharing suggested that within-population genomic prediction and GWAS were poor because allele frequencies of causal loci and linked markers differed among populations. Given the urgent need to conserve natural populations and ecosystems, our results suggest that climate variables alone can be used to predict population phenotypes, delineate seed zones and deployment zones, and guide assisted migration.

Science & Technology - Other Topics↗

Steelhead ( Oncorhynchus mykiss ) lineages and sexes show variable patterns of association of adult migration timing and age‐at‐maturity traits with two genomic regions

Abstract As life history diversity plays a critical role in supporting the resilience of exploited populations, understanding the genetic basis of those life history variations is important for conservation management. However, effective application requires a robust understanding of the strength and universality of genetic associations. Here, we examine genetic variation of single nucleotide polymorphisms in genomic regions previously associated with migration phenology and age‐at‐maturity in steelhead ( Oncorhynchus mykiss ) from the Columbia River. We found chromosome 28 markers (GREB1L, ROCK1 genes) explained significant variance in migration timing in both coastal and inland steelhead. However, strength of association was much greater in coastal than inland steelhead ( R 2 0.51 vs. 0.08), suggesting that genomic background and challenging inland migration pathways may act to moderate effects of this region. Further, we found that chromosome 25 candidate markers (SIX6 gene) were significantly associated with age and size at first return migration for inland steelhead, and this pattern was mediated by sex in a predictable pattern (males R 2 = 0.139–0.170; females R 2 = 0.096–0.111). While this encourages using these candidate regions in predicting life history characteristics, we suggest that stock‐specific associations and haplotype frequencies will be useful in guiding implementation of genetic assays to inform management.

Willis, Stuart C.↗