Pathogenic Bacillus anthracis in the progressive gene losses and gains in adaptive evolution

Subtyping Social Determinants of Health in All of Us: Network Analysis and Visualization Approach

Background

Social determinants of health (SDoH), such as financial resources and housing stability, account for between 30-55% of people's health outcomes. While many studies have identified strong associations among specific SDoH and health outcomes, most people experience multiple SDoH that impact their daily lives. Analysis of this complexity requires the integration of personal, clinical, social, and environmental information from a large cohort of individuals that have been traditionally underrepresented in research, which is only recently being made available through the All of Us research program. However, little is known about the range and response of SDoH in All of Us, and how they co-occur to form subtypes, which are critical for designing targeted interventions.

Objective

To address two research questions: (1) What is the range and response to survey questions related to SDoH in the All of Us dataset? (2) How do SDoH co-occur to form subtypes, and what are their risk for adverse health outcomes?

Methods

For Question-1, an expert panel analyzed the range of SDoH questions across the surveys with respect to the 5 domains in Healthy People 2030 (HP-30), and analyzed their responses across the full All of Us data (n=372,397, V6). For Question-2, we used the following steps: (1) due to the missingness across the surveys, selected all participants with valid and complete SDoH data, and used inverse probability weighting to adjust their imbalance in demographics compared to the full data; (2) an expert panel grouped the SDoH questions into SDoH factors for enabling a more consistent granularity; (3) used bipartite modularity maximization to identify SDoH biclusters, their significance, and their replicability; (4) measured the association of each bicluster to three outcomes (depression, delayed medical care, emergency room visits in the last year) using multiple data types (surveys, electronic health records, and zip codes mapped to Medicaid expansion states); and (5) the expert panel inferred the subtype labels, potential mechanisms that precipitate adverse health outcomes, and interventions to prevent them.

Results

For Question-1, we identified 110 SDoH questions across 4 surveys, which covered all 5 domains in HP-30. However, the results also revealed a large degree of missingness in survey responses (1.76%-84.56%), with later surveys having significantly fewer responses compared to earlier ones, and significant differences in race, ethnicity, and age of participants of those that completed the surveys with SDoH questions, compared to those in the full All of Us dataset. Furthermore, as the SDoH questions varied in granularity, they were categorized by an expert panel into 18 SDoH factors. For Question-2, the subtype analysis (n=12,913, d=18) identified 4 biclusters with significant biclusteredness (Q=0.13, random-Q=0.11, z=7.5, P<0.001), and significant replication (Real-RI=0.88, Random-RI=0.62, P<.001). Furthermore, there were statistically significant associations between specific subtypes and the outcomes, and with Medicaid expansion, each with meaningful interpretations and potential targeted interventions. For example, the subtype Socioeconomic Barriers included the SDoH factors not employed, food insecurity, housing insecurity, low income, low literacy, and low educational attainment, and had a significantly higher odds ratio (OR=4.2, CI=3.5-5.1, P-corr<.001) for depression, when compared to the subtype Sociocultural Barriers. Individuals that match this subtype profile could be screened early for depression and referred to social services for addressing combinations of SDoH such as housing insecurity and low income. Finally, the identified subtypes spanned one or more HP-30 domains revealing the difference between the current knowledge-based SDoH domains, and the data-driven subtypes.

Conclusions

The results revealed that the SDoH subtypes not only had statistically significant clustering and replicability, but also had significant associations with critical adverse health outcomes, which had translational implications for designing targeted SDoH interventions, decision-support systems to alert clinicians of potential risks, and for public policies. Furthermore, these SDoH subtypes spanned multiple SDoH domains defined by HP-30 revealing the complexity of SDoH in the real-world, and aligning with influential SDoH conceptual models such as by Dahlgren-Whitehead. However, the high-degree of missingness warrants repeating the analysis as the data becomes more complete. Consequently we designed our machine learning code to be generalizable and scalable, and made it available on the All of Us workbench, which can be used to periodically rerun the analysis as the dataset grows for analyzing subtypes related to SDoH, and beyond.

Molecular and Genomic Characterization of PFAB2: A Non-virulent Bacillus anthracis Strain Isolated from an Indian Hot Spring

Background

Thermophilic bacilli in both aerobic or facultative anaerobic forms have been isolated for over a hundred years from different mesophilic or thermophilic environments as they are potential source of bioactive secondary metabolites. But the taxonomic resolution in the Bacillus genus at species or at strain level is very challenging for the insufficient divergence of the 16S rRNA genes. One such recurring problem is among Bacillus anthracis, B. cereus and B. thuringiensis. The disease-causing B. anthracis strains have their characteristic virulence factors coded in two well-known plasmids, namely pXO1 (toxin genes) and pXO2 (capsule genes).

Objective

The present study aimed at the molecular and genomic characterization of a recently reported thermophilic and environmental isolate of B. anthracis, strain PFAB2.

Methods

We performed comparative genomics between the PFAB2 genome and different strains of B. anthracis, along with closely related B. cereus strains.

Results

The pangenomic analysis suggests that the PFAB2 genome harbors no complete prophage genes. Cluster analysis of Bray-Kurtis similarity resemblance matrix revealed that gene content of PFAB2 is more closely related to other environmental strains of B. anthracis. The secretome analysis and the in vitro and in vivo pathogenesis experiments corroborate the avirulent phenotype of this strain. The most probable explanation for this phenotype is the apparent absence of plasmids harboring genes for capsule biosynthesis and toxins secretion in the draft genome. Additional features of PFAB2 are good spore-forming and germinating capabilities and rapid replication ability.

Conclusion

The high replication rate in a wide range of temperatures and culture media, the non-pathogenicity, the good spore forming capability and its genomic similarity to the Ames strain together make PFAB2 an interesting model strain for the study of the pathogenic evolution of B. anthracis.

ORCAN-a web-based meta-server for real-time detection and functional annotation of orthologs

Summary

ORCAN (ORtholog sCANner) is a web-based meta-server for one-click evolutionary and functional annotation of protein sequences. The server combines information from the most popular orthology-prediction resources, including four tools and four online databases. Functional annotation utilizes five additional comparisons between the query and identified homologs, including: sequence similarity, protein domain architectures, functional motifs, Gene Ontology term assignments and a list of associated articles. Furthermore, the server uses a plurality-based rating system to evaluate the orthology relationships and to rank the reference proteins by their evolutionary and functional relevance to the query. Using a dataset of ∼1 million true yeast orthologs as a sample reference set, we show that combining multiple orthology-prediction tools in ORCAN increases the sensitivity and precision by 1-2 percent points.

Availability and Implementation

The service is available for free at http://www.combio.pl/orcan/ .

Contact

wmk@amu.edu.pl.

Supplementary information

Supplementary data are available at Bioinformatics online.

Resolution and reconciliation of non-binary gene trees with transfers, duplications and losses

Summary

Gene trees reconstructed from sequence alignments contain poorly supported branches when the phylogenetic signal in the sequences is insufficient to determine them all. When a species tree is available, the signal of gains and losses of genes can be used to correctly resolve the unsupported parts of the gene history. However finding a most parsimonious binary resolution of a non-binary tree obtained by contracting the unsupported branches is NP-hard if transfer events are considered as possible gene scale events, in addition to gene origination, duplication and loss. We propose an exact, parameterized algorithm to solve this problem in single-exponential time, where the parameter is the number of connected branches of the gene tree that show low support from the sequence alignment or, equivalently, the maximum number of children of any node of the gene tree once the low-support branches have been collapsed. This improves on the best known algorithm by an exponential factor. We propose a way to choose among optimal solutions based on the available information. We show the usability of this principle on several simulated and biological datasets. The results are comparable in quality to several other tested methods having similar goals, but our approach provides a lower running time and a guarantee that the produced solution is optimal.

Availability and Implementation

Our algorithm has been integrated into the ecceTERA phylogeny package, available at http://mbb.univ-montp2.fr/MBB/download_sources/16__ecceTERA and which can be run online at http://mbb.univ-montp2.fr/MBB/subsection/softExec.php?soft=eccetera .

Contact

celine.scornavacca@umontpellier.fr.

Supplementary information

Supplementary data are available at Bioinformatics online.

Draft Genome Sequence of the Nonpathogenic, Thermotolerant, and Exopolysaccharide-Producing Bacillus anthracis Strain PFAB2 from Panifala Hot Water Spring in West Bengal, India

Bacillus anthracis is the causative agent of fatal anthrax in both animals and humans. It is prevalently pathogenic. Here, we present a Bacillus anthracis PFAB2 strain from a relatively unexplored Panifala hot water spring in West Bengal, India. It is nonpathogenic, exopolysaccharide producing, and thermotolerant in nature.

Gnom(Cmp): a quantitative approach for comparative analysis of closely related genomes of bacterial pathogens

Comparative genome analysis is a powerful approach to understanding the biology of infectious bacterial pathogens. In this study, a quantitative approach, referred to as Gnom(Cmp), was developed to study the microevolution of bacterial pathogens. Although much more time-consuming than existing tools, this procedure provides a much higher resolution. Gnom(Cmp) accomplishes this by establishing genome-wide heterogeneity genotypes, which are then quantified and comparatively analyzed. The heterogeneity genotypes are defined as chromosomal base positions that have multiple variants within particular genomes, resulted from DNA duplications and subsequent mutations. To prove the concept, the procedure was applied on the genomes of 15 Staphylococcus aureus strains, focusing extensively on two pairs of hVISA/VISA strains. hVISA refers to heteroresistant vancomycin-intermediate S. aureus strains and VISA is their VISA mutants. hVISA/VISA displays some remarkable properties. hVISA is susceptible to vancomycin, but VISA mutants emerge soon after a short period of vancomycin therapy, therefore making the pathogen a great model organism for fast-evolving bacterial pathogens. The analysis indicated that Gnom(Cmp) could reveal variants within the genomes, which can be analyzed within the global genome context. Gnom(Cmp) discovered evolutionary hotspots and their dynamics among many closely related, even isogenic genomes. The analysis thus allows the exploration of the molecular mechanisms behind hVISA/VISA evolution, providing a working hypotheses for experimental testing and validation.

Viability of Bacillus licheniformis and Bacillus thuringiensis spores as a model for predicting the fate of bacillus anthracis spores during composting of dead livestock

Safe disposal of dead livestock and contaminated manure is essential for the effective control of infectious disease outbreaks. Composting has been shown to be an effective method of disposal, but no information exists on its ability to contain diseases caused by spore-forming bacteria, such as Bacillus anthracis. Duplicate composters (east and west), each containing 16 dead cattle, were constructed (final capacity, 85,000 kg). Spores (10(7) CFU/g manure) of Bacillus licheniformis and Bacillus thuringiensis were mixed with autoclaved feedlot manure and placed in either sterile vials or porous nylon bags. Compost temperatures in the west composter were slightly higher than in the east composter. Viable B. thuringiensis spores were reduced to ≤10(2) CFU in all samples after 112 days but were isolated from bags (west composter) at ≤10(2) and at 10(5) CFU (east composter) after 230 days. In contrast, B. licheniformis was at ≤10(2) CFU in vials (west composter) after 112 days but remained at 10(6) CFU after 230 days (east composter). Similarly, B. licheniformis in bags was not detected after 230 days in the west composter but remained at 10(7) CFU in the east composter. Our study suggests that spore viability was reduced in the west composter by exposure to compost and elevated temperatures over time. Different temperature profiles may explain why spores remained viable in the east structure but were largely rendered nonviable in the west structure. Under practical conditions, variation in composting microclimates may preclude the complete inactivation of Bacillus spores, including those of B. anthracis, during composting. However, composting may still have merit as a method of biocontainment, reducing and diluting the transfer of infectious spores into the environment.

Microbial threat lists: obstacles in the quest for biosecurity?

The Select Agents and Toxins List was created by the US Government to limit the possession of and access to particular microorganisms and toxins. Casadevall and Relman argue that this list, and others like it, could have the paradoxical effect of increasing our vulnerability to biological attack and natural epidemics.

Anxiety about threats from the microbial world and about the deliberate misuse of microorganisms has led to efforts to define and control these dangers using lists and regulations. One list with tremendous legal implications and a potentially huge impact on research is the Select Agents and Toxins List, which was created by the US Government to limit the possession of and access to particular microorganisms and toxins. In this article, in addition to highlighting general problems with taxonomy-based, microorganism-centric lists, we discuss our view that such lists may have the paradoxical effect of increasing the societal vulnerability to biological attack and natural epidemics by interfering with the sharing of microbial samples and hindering research on vaccines and therapeutics.

Transcriptional profiling of Bacillus anthracis Sterne (34F2) during iron starvation

Lack of available iron is one of many environmental challenges that a bacterium encounters during infection and adaptation to iron starvation is important for the pathogen to efficiently replicate within the host. Here we define the transcriptional response of B. anthracis Sterne (34F₂) to iron depleted conditions. Genome-wide transcript analysis showed that B. anthracis undergoes considerable changes in gene expression during growth in iron-depleted media, including the regulation of known and candidate virulence factors. Two genes encoding putative internalin proteins were chosen for further study. Deletion of either gene (GBAA0552 or GBAA1340) resulted in attenuation in a murine model of infection. This attenuation was amplified in a double mutant strain. These data define the transcriptional changes induced during growth in low iron conditions and illustrate the potential of this dataset in the identification of putative virulence determinants for future study.