The natural assemblage of a symbiotic bacterial microbiome (bacteriome) with microalgae in marine ecosystems is now being investigated as a means to increase algal productivity for industry. When algae are grown in open pond settings, biological contamination causes an estimated 30% loss of the algal crop. Therefore, new crop protection strategies that do not disrupt the native algal bacteriome are needed to produce reliable, high-yield algal biomass. Bacteriophages offer an unexplored solution to treat bacterial pathogenicity in algal cultures because they can eliminate a single species without affecting the bacteriome. To address this, we identified a highly virulent pathogen of the microalga Nannochloropsis gaditana, the bacterium Bacillus safensis, and demonstrated rescue of the microalgae from the pathogen using phage. 16S rRNA amplicon sequencing showed that phage treatment did not alter the composition of the bacteriome. It is widely suspected that the algal bacteriome could play a protective role against bacterial pathogens. To test this, we compared the susceptibility of a bacteriome-attenuated N. gaditana culture challenged with B. safensis to a N. gaditana culture carrying a growth-promoting bacteriome. We showed that the loss of the bacteriome increased the susceptibility of N. gaditana to the pathogen. Transplanting the microalgal bacteriome to the bacteriome-attenuated culture reconstituted the protective effect of the bacteriome. Finally, the success of phage treatment was dependent on the presence of beneficial bacteriome. This study introduces two synergistic countermeasures against bacterial pathogenicity in algal cultures and a tractable model for studying interactions between microalgae, phages, pathogens, and the algae microbiome.
New approaches to preventing and treating infections, particularly of the respiratory tract, are needed. One promising strategy is to reconfigure microbial communities (microbiomes) within the host to improve defense against pathogens. Probiotics and prebiotics for gastrointestinal (GI) infections offer a template for success. We sought to develop comparable countermeasures for respiratory infections. First, we characterized interactions between the airway microbiome and a biodefense-related respiratory pathogen (Burkholderia thailandensis; Bt), using a mouse model of infection. Then, we recovered microbiome constituents from the airway and assessed their ability to re-colonize the airway and protect against respiratory Bt infection. We found that microbiome constituents belonging to Bacillus and related genuses frequently displayed colonization and anti-Bt activity. Comparative growth requirement profiling of these Bacillus strains vs Bt enabled identification of candidate prebiotics. This work serves as proof of concept for airway probiotics, as well as a strong foundation for development of airway prebiotics.
This report describes research conducted to use data science and machine learning methods to distinguish targeted genome editing versus natural mutation and sequencer machine noise. Genome editing capabilities have been around for more than 20 years, and the efficiencies of these techniques has improved dramatically in the last 5+ years, notably with the rise of CRISPR-Cas technology. Whether or not a specific genome has been the target of an edit is concern for U.S. national security. The research detailed in this report provides first steps to address this concern. A large amount of data is necessary in our research, thus we invested considerable time collecting and processing it. We use an ensemble of decision tree and deep neural network machine learning methods as well as anomaly detection to detect genome edits given either whole exome or genome DNA reads. The edit detection results we obtained with our algorithms tested against samples held out during training of our methods are significantly better than random guessing, achieving high F1 and recall scores as well as with precision overall.
The mobilome of a microbe, i.e., its set of mobile elements, has major effects on its ecology, and is important to delineate properly in each genome. This becomes more challenging for incomplete genomes, and even more so for metagenome-assembled genomes (MAGs), where misbinning of scaffolds and other losses can occur. Genomic islands (GIs), which integrate into the host chromosome, are a major component of the mobilome. Our GI-detection software TIGER, unique in its precise mapping of GI termini, was applied to 74,561 genomes from 2,473 microbial species, each species containing at least one MAG and one isolate genome. A species-normalized deficit of ∼1.6 GIs/genome was measured for MAGs relative to isolates. To test whether this undercount was due to the higher fragmentation of MAG genomes, TIGER was updated to enable detection of split GIs whose termini are on separate scaffolds or that wrap around the origin of a circular replicon. This doubled GI yields, and the new split GIs matched the quality of single-scaffold GIs, except that highly fragmented GIs may lack central portions. Cross-scaffold search is an important upgrade to GI detection as fragmented genomes increasingly dominate public databases. TIGER2 better captures MAG microdiversity, recovering niche-defining GIs and supporting microbiome research aims such as virus-host linking and ecological assessment.
This project tackles the antibiotic resistance crisis, developing a new method for discovering numerous efficacious bacteriophages for therapeutic cocktails against bacterial pathogens. The phage therapy approach to infectious disease, recently rekindled in U.S. medicine, requires numerous phages for each bacterial pathogen. Our approach 1) uses Sandia-unique software to identify dormant phages (prophages) integrated into bacterial chromosomes, 2) identifies prophage-laden bacteria that are close relatives of the target pathogenic strain to be killed, and 3) engineers away properties of these phages that are undesirable for therapy. We have perfected our phage-finding software, implemented our phage therapy strategy by targeting the pathogen Pseudomonas aeruginosa, and prepared new software to assist the phage engineering. We then turned toward Burkholderia pathogens, aiming to overcome the difficulty to transform these bacteria with a novel phage conjugation approach. Our work demonstrates the validity of a new approach to phage therapy for killing antibiotic resistant pathogens.
We present the draft genome sequences of three Burkholderia thailandensis strains, E421, E426, and DW503. E421 consists of 90 contigs of 6,639,935 bp and 67.73% GC content. E426 consists of 106 contigs of 6,587,853 bp and 67.73% GC content. DW503 consists of 102 contigs of 6,458,767 bp and 67.64% GC content.
Sandia National Laboratories currently has 27 COVID-related Laboratory Directed Research & Development (LDRD) projects focused on helping the nation during the pandemic. These LDRD projects cross many disciplines including bioscience, computing & information sciences, engineering science, materials science, nanodevices & microsystems, and radiation effects & high energy density science.
Bacterial tRNA have been found interrupted at various positions in the anticodon loop by group I introns, in four types. The primary bioinformatic tool for group I intron discovery is a covariance model that can identify conserved features in the catalytic core and can sometimes identify the typical uridine residue at the -1 position, preceding the 5-prime splice site, but cannot identify the typical guanidine residue at the omega position, preceding the 3-prime splice site, to achieve precise mapping. One approach to complete the automation of group I intron mapping is to focus instead on the exons, which is enabled by the regularity of tRNAs. We develop a software module, within a larger package (tFind) aimed at mapping bacterial tRNA and tmRNA genes precisely, that expands this list of four known classes of intron-interrupted tRNAs to 21 cases. A new covariance model for these introns is presented. The wobble base pair formed by the -1 uridine is considered a determinant of the 5-prime splice site, yet one reasonably large new type bears a cytidine nucleotide at that position.
When analyzing pathogen transcriptomes during the infection of host cells, the signal-to-background (pathogen-to-host) ratio of nucleic acids (NA) in infected samples is very small. Despite the advancements in next-generation sequencing, the minute amount of pathogen NA makes standard RNA-seq library preps inadequate for effective gene-level analysis of the pathogen in cases with low bacterial loads. In order to provide a more complete picture of the pathogen transcriptome during an infection, we developed a novel pathogen enrichment technique, which can enrich for transcripts from any cultivable bacteria or virus, using common, readily available laboratory equipment and reagents. To evenly enrich for pathogen transcripts, we generate biotinylated pathogen-targeted capture probes in an enzymatic process using the entire genome of the pathogen as a template. The capture probes are hybridized to a strand-specific cDNA library generated from an RNA sample. The biotinylated probes are captured on a monomeric avidin resin in a miniature spin column, and enriched pathogen-specific cDNA is eluted following a series of washes. To test this method, we performed an in vitro time-course infection using Klebsiella pneumoniae to infect murine macrophage cells. K. pneumoniae transcript enrichment efficiency was evaluated using RNA-seq. Bacterial transcripts were enriched up to ∼400-fold, and allowed the recovery of transcripts from ∼2000-3600 genes not observed in untreated control samples. These additional transcripts revealed interesting aspects of K. pneumoniae biology including the expression of putative virulence factors and the expression of several genes responsible for antibiotic resistance even in the absence of drugs.
RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality.
Virulence genes on mobile DNAs such as genomic islands (GIs) and plasmids promote bacterial pathogen emergence. Excision is an early step in GI mobilization, producing a circular GI and a deletion site in the chromosome; circular forms are also known for some bacterial insertion sequences (ISs). The recombinant sequence at the junctions of such circles and deletions can be detected sensitively in high-throughput sequencing data, using new computational methods that enable empirical discovery of mobile DNAs. For the rich mobilome of a hospital Klebsiella pneumoniae strain, circularization junctions (CJs) were detected for six GIs and seven IS types. Our methods revealed differential biology of multiple mobile DNAs, imprecision of integrases and transposases, and differential activity among identical IS copies for IS26, ISKpn18 and ISKpn21. Using the resistance of circular dsDNA molecules to exonuclease, internally calibrated with the native plasmids, showed that not all molecules bearing GI CJs were circular. Transpositions were also detected, revealing replicon preference (ISKpn18 prefers a conjugative IncA/C2 plasmid), local action (IS26), regional preferences, selection (against capsule synthesis) and IS polarity inversion. Efficient discovery and global characterization of numerous mobile elements per experiment improves accounting for the new gene combinations that arise in emerging pathogens.
Lane, Todd; Lane, Pamela; Williams, Kelly P.; Wilkenfeld, Joshua S.; Solberg, Owen D.; Fuqua, Zachary B.; Cornelius, Nina G.; Gillespie, Shaunette; Samocha, Tzachi M.; Carney, Laura T.
Productivity of algal mass culture can be severely reduced by contaminating organisms. It is, therefore, important to identify contaminants, determine their effect on productivity and, ultimately, develop countermeasures against such contamination. In the present study we utilized microbiome analysis by second-generation sequencing of small subunit rRNA genes to characterize the predator and pathogen burden of open raceway cultures of Nannochloropsis salina. Samples were analyzed from replicate raceways before and after crashes. In one culture cycle, we identified two algivorous species, the rotifer Brachionus and gastrotrich Chaetonotus, the presence of which may have contributed to the loss of algal biomass. In the second culture cycle, the raceways were treated with hypochlorite in an unsuccessful attempt to interdict the crash. Our analyses were shown to be an effective strategy for the identification of the biological contaminants and the characterization of intervention strategies.
Here, we present the draft genome sequence of Burkholderia pseudomallei PHLS 6, a virulent clinical strain isolated from a melioidosis patient in Bangladesh in 1960. The draft genome consists of 39 contigs and is 7,322,181 bp long.
Yersinia enterocolitica is typically considered an extracellular pathogen; however, during the course of an infection, a significant number of bacteria are stably maintained within host cell vacuoles. Little is known about this population and the role it plays during an infection. To address this question and to elucidate the spatially and temporally dynamic gene expression patterns of Y. enterocoliticabiovar 1B through the course of an in vitro infection, transcriptome sequencing and differential gene expression analysis of bacteria infecting murine macrophage cells were performed under four distinct conditions. Bacteria were first grown in a nutrient-rich medium at 26°C to establish a baseline of gene expression that is unrelated to infection. The transcriptomes of these bacteria were then compared to bacteria grown in a conditioned cell culture medium at 37°C to identify genes that were differentially expressed in response to the increased temperature and medium but not in response to host cells. Infections were then performed, and the transcriptomes of bacteria found on the extracellular surface and intracellular compartments were analyzed individually. The upregulated genes revealed potential roles for a variety of systems in promoting intracellular virulence, including the Ysa type III secretion system, the Yts2 type II secretion system, and the Tad pilus. It was further determined that mutants of each of these systems had decreased virulence while infecting macrophages. Overall, these results reveal the complete set of genes expressed by Y. enterocolitica in response to infection and provide the groundwork for future virulence studies.
Genomic islands are mobile DNAs that are major agents of bacterial and archaeal evolution. Integration into prokaryotic chromosomes usually occurs site-specifically at tRNA or tmRNA gene (together, tDNA) targets, catalyzed by tyrosine integrases. This splits the target gene, yet sequences within the island restore the disrupted gene; the regenerated target and its displaced fragment precisely mark the endpoints of the island. We applied this principle to search for islands in genomic DNA sequences. Our algorithm identifies tDNAs, finds fragments of those tDNAs in the same replicon and removes unlikely candidate islands through a series of filters. A search for islands in 2168 whole prokaryotic genomes produced 3919 candidates. The website Islander (recentlymoved to http://bioinformatics.sandia.gov/islander/) presents these precisely mapped candidate islands, the gene content and the island sequence. The algorithm further insists that each island encode an integrase, and attachment site sequence identity is carefully noted; therefore, the database also serves in the study of integrase site-specificity and its evolution.
The transfer-messenger RNA (tmRNA) and its partner protein SmpB act together in resolving problems arising when translating bacterial ribosomes reach the end of mRNA with no stop codon. Their genes have been found in nearly all bacterial genomes and in some organelles. The tmRNA Website serves tmRNA sequences, alignments and feature annotations, and has recently moved to http://bioinformatics.sandia.gov/tmrna/. New features include software used to find the sequences, an update raising the number of unique tmRNA sequences from 492 to 1716, and a database of SmpB sequences which are served along with the tmRNA sequence from the same organism.
The field of non-coding RNA biology has been hampered by the lack of availability of a comprehensive, up-to-date collection of accessioned RNA sequences. Here we present the first release of RNAcentral, a database that collates and integrates information from an international consortium of established RNA sequence databases. The initial release contains over 8.1 million sequences, including representatives of all major functional classes. A web portal (http://rnacentral.org) provides free access to data, search functionality, cross-references, source code and an integrated genome browser for selected species.
Genes for the RNA tmRNA and protein SmpB, partners in the trans-translation process that rescues stalled ribosomes, have previously been found in all bacteria and some organelles. We validate recent identification of tmRNA homologs in oomycete mitochondria by finding partner genes from oomycete nuclei that target SmpB to the mitochondrion. Exhaustive search now identifies a small number of complete, often highly derived, bacterial genomes that appear to lack a functional copy of one or the other partner gene (but not both). Three groups with reduced genomes have lost the central loop of SmpB, which is thought to improve alanylation and EF-Tu activation: Carsonella, Hodgkinia and the hemplasmas (hemotropic Mycoplasma). Carsonella has also lost the SmpB C-terminal tail, thought to stimulate the decoding center of the ribosome. Carsonella moreover exhibits gene overlap such that tmRNA maturation should produce a non-stop smpB mRNA, and one isolate exhibits complete degradation of the tmRNA gene yet its smpB shows no evidence for relaxed selective constraint. After loss of the SmpB central loop in the hemoplasmas, a subclade apparently lost tmRNA. At least some of the tmRNA/SmpB-deficient strains appear to further lack the ArfA and ArfB backup systems for ribosome rescue. The most frequent neighbors of smpB are the tmRNA gene, a ratA/rnfH unit, and the gene for RNaseR, a known physical and functional partner of tmRNA-SmpB. The tmRNA Website has moved and been updated, adding an SmpB sequence database (http://bioinformatics.sandia.gov/tmrna).
Lignin is often overlooked in the valorization of lignocellulosic biomass, but lignin-based materials and chemicals represent potential value-added products for biorefineries that could significantly improve the economics of a biorefinery. Fluctuating crude oil prices and changing fuel specifications are some of the driving factors to develop new technologies that could be used to convert polymeric lignin into low molecular weight lignin and or monomeric aromatic feedstocks to assist in the displacement of the current products associated with the conversion of a whole barrel of oil. Our project of understanding microbial lignolysis for renewable platform chemicals aimed to understand microbial and enzymatic lignolysis processes to break down lignin for conversion into commercially viable drop-in fuels. We developed novel lignin analytics to interrogate enzymatic and microbial lignolysis of native polymeric lignin and established a detailed understanding of lignolysis as a function of fungal enzyme, microbes and endophytes. Bioinformatics pipeline was developed for metatranscryptomic analysis of aridland ecosystem for investigating the potential discovery of new lignolysis gene and gene products.
Key goals towards national biosecurity include methods for analyzing pathogens, predicting their emergence, and developing countermeasures. These goals are served by studying bacterial genes that promote pathogenicity and the pathogenicity islands that mobilize them. Cyberinfrastructure promoting an island database advances this field and enables deeper bioinformatic analysis that may identify novel pathogenicity genes. New automated methods and rich visualizations were developed for identifying pathogenicity islands, based on the principle that islands occur sporadically among closely related strains. The chromosomally-ordered pan-genome organizes all genes from a clade of strains; gaps in this visualization indicate islands, and decorations of the gene matrix facilitate exploration of island gene functions. A %E2%80%9Clearned phyloblocks%E2%80%9D method was developed for automated island identification, that trains on the phylogenetic patterns of islands identified by other methods. Learned phyloblocks better defined termini of previously identified islands in multidrug-resistant Klebsiella pneumoniae ATCC BAA-2146, and found its only antibiotic resistance island.
