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.