A machine learning-based typing scheme refinement for Listeria monocytogenes core genome multilocus sequence typing with high discriminatory power for common source outbreak tracking

Background As whole-genome sequencing for pathogen genomes becomes increasingly popular, the typing methods of gene-by-gene comparison, such as core genome multilocus sequence typing (cgMLST) and whole-genome multilocus sequence typing (wgMLST), are being routinely implemented in molecular epidemiology. However, some intrinsic problems remain. For example, genomic sequences with varying read depths, read lengths, and assemblers influence the genome assemblies, introducing error or missing alleles into the generated allelic profiles. These errors and missing alleles might create “specious discrepancy” among closely related isolates, thus making accurate epidemiological interpretation challenging. In addition, the rapid growth of the cgMLST allelic profile database can cause problems related to storage and maintenance as well as long query search times. Methods We attempted to resolve these issues by decreasing the scheme size to reduce the occurrence of error and missing alleles, alleviate the storage burden, and improve the query search time. The challenge in this approach is maintaining the typing resolution when using fewer loci. We achieved this by using a popular artificial intelligence technique, XGBoost, coupled with Shapley additive explanations for feature selection. Finally, 370 loci from the original 1701 cgMLST loci of Listeria monocytogenes were selected. Results Although the size of the final scheme (LmScheme_370) was approximately 80% lower than that of the original cgMLST scheme, its discriminatory power, tested for 35 outbreaks, was concordant with that of the original cgMLST scheme. Although we used L. monocytogenes as a demonstration in this study, the approach can be applied to other schemes and pathogens. Our findings might help elucidate gene-by-gene–based epidemiology.

geneCo: a visualized comparative genomic method to analyze multiple genome structures

Summary In comparative and evolutionary genomics, a detailed comparison of common features between organisms is essential to evaluate genetic distance. However, identifying differences in matched and mismatched genes among multiple genomes is difficult using current comparative genomic approaches due to complicated methodologies or the generation of meager information from obtained results. This study describes a visualized software tool, geneCo (gene Comparison), for comparing genome structure and gene arrangements between various organisms. User data are aligned, gene information is recognized, and genome structures are compared based on user-defined GenBank files. Information regarding inversion, gain, loss, duplication and gene rearrangement among multiple organisms being compared is provided by geneCo, which uses a web-based interface that users can easily access without any need to consider the computational environment. Availability and implementation Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/geneCo. The main module of geneCo is implemented by Python and the web-based user interface is built by PHP, HTML and CSS to support all browsers. Supplementary information Supplementary data are available at Bioinformatics online.

Diversity of Tropical Marine Macroalgae from Coastal Area of Sayang Heulang, West Java Indonesia

Genetic diversity of nine marine macroalgae from coastal area of Sayang Heulang were assessed based on phenotypic and ribotyping analysis. Morphology of the macroalgaes were classified based on the color of the organism such as red (4 samples), brown (3 samples) and green (2 samples). Genomic DNA from the organisms were isolated using CTAB method with slight modification. The 18S rRNA gene amplified by PCR method using standar primers for V4 region of 18S rRNA gene. The amplicons were sequenced and analysed. The results showed that all the sequences are closed to V4 region of 18S rRNA gene. Comparison among the nine sequences showed a variation of homology. The best homology was shown by the sequence of SB and TC (99,1%), both are brown color macroalgea. The lowest homology was shown by GU (red color) and TC (brown color) with the homology at around 64,6%. Further analysis by comparing among the same color and the cross color showed that the same color does not show genetically close each other. Phylogenic analysis showed that the three brown colors are closed each other, however the rest are seen different and far away each other.

Genome-Wide Identification of Host-Segregating Epidemiological Markers for Source Attribution in Campylobacter jejuni

ABSTRACT Campylobacter is among the most common worldwide causes of bacterial gastroenteritis. This organism is part of the commensal microbiota of numerous host species, including livestock, and these animals constitute potential sources of human infection. Molecular typing approaches, especially multilocus sequence typing (MLST), have been used to attribute the source of human campylobacteriosis by quantifying the relative abundance of alleles at seven MLST loci among isolates from animal reservoirs and human infection, implicating chicken as a major infection source. The increasing availability of bacterial genomes provides data on allelic variation at loci across the genome, providing the potential to improve the discriminatory power of data for source attribution. Here we present a source attribution approach based on the identification of novel epidemiological markers among a reference pan-genome list of 1,810 genes identified by gene-by-gene comparison of 884 genomes of Campylobacter jejuni isolates from animal reservoirs, the environment, and clinical cases. Fifteen loci involved in metabolic activities, protein modification, signal transduction, and stress response or coding for hypothetical proteins were selected as host-segregating markers and used to attribute the source of 42 French and 281 United Kingdom clinical C. jejuni isolates. Consistent with previous studies of British campylobacteriosis, analyses performed using STRUCTURE software attributed 56.8% of British clinical cases to chicken, emphasizing the importance of this host reservoir as an infection source in the United Kingdom. However, among French clinical isolates, approximately equal proportions of isolates were attributed to chicken and ruminant reservoirs, suggesting possible differences in the relative importance of animal host reservoirs and indicating a benefit for further national-scale attribution modeling to account for differences in production, behavior, and food consumption. IMPORTANCE Accurately quantifying the relative contribution of different host reservoirs to human Campylobacter infection is an ongoing challenge. This study, based on the development of a novel source attribution approach, provides the first results of source attribution in Campylobacter jejuni in France. A systematic analysis using gene-by-gene comparison of 884 genomes of C. jejuni isolates, with a pan-genome list of genes, identified 15 novel epidemiological markers for source attribution. The different proportions of French and United Kingdom clinical isolates attributed to each host reservoir illustrate a potential role for local/national variations in C. jejuni transmission dynamics.

Compatibility and Conjugacy on Partial Arrays

Research in combinatorics on words goes back a century. Berstel and Boasson introduced the partial words in the context of gene comparison. Alignment of two genes can be viewed as a construction of two partial words that are said to be compatible. In this paper, we examine to which extent the fundamental properties of partial words such as compatbility and conjugacy remain true for partial arrays. This paper studies a relaxation of the compatibility relation calledk-compability. It also studiesk-conjugacy of partial arrays.

Inheritance Pattern of Temephos Resistance, an Organophosphate Insecticide, in Aedes aegypti (L.)

The present paper reports the mode of inheritance of resistance in laboratory induced temephos resistant and susceptible strains of Ae. aegypti. Homozygous resistant and susceptible strains of Ae. aegypti were generated by selective inbreeding at a diagnostic dose of 0.02 mg/L of temephos. Genetic crosses were carried out between these strains to determine the inheritance pattern of temephos resistance. The log-dosage probit mortality relationships and degree of dominance (D) were calculated. The dosage-mortality (d-m) line of the F1 generation was nearer to the resistant parent than the susceptible one. The “D” value was calculated as 0.15 indicating that the temephos resistant gene is incompletely dominant. The d-m lines of the F2 generation and progeny from the backcross exhibited clear plateaus of mortality across a range of doses indicating that temephos resistance is controlled by a single gene. Comparison of the mortality data with the theoretical expectations using the χ2 test revealed no significant difference, confirming a monogenic pattern of inheritance. In conclusion, the study provides evidence that the temephos resistance in Ae. aegypti follows an incompletely dominant and monogenic mode of inheritance.

Multitudes of perspectives: Integrating the Selfish Goal model with views on scientific metaphors, goal systems, and society

In our response, we address commentators' feedback regarding the contributions and limitations of the Selfish Goal model. We first clarify potential misunderstandings regarding the model's contributions and the role of consciousness. Second, we situate evaluations of the selfish metaphor within the similarities and differences inherent to the goal-gene comparison. We then respond to commentators' insights regarding future directions and implications of our model, particularly with respect to the broader organizational systems in which goals may operate. Finally, we reiterate important considerations for goal research moving forward.