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The RNA-Seq method has become a key tool in transcriptomics, providing deep insight into the genetic functioning of organisms. It is essential for understanding how genes are expressed, for discovering new gene variants and for understanding pathologies at the genetic level. RNA-Seq simulators are great for testing and validating bioinformatics tools, they offer a way to compare different computational algorithms and allow examining different sequencing protocols, parameter settings and sample sizes to ensure the most efficient use of resources. This study introduces BacSeqer, an RNA-Seq simulator specifically designed for bacterial transcriptomes with the aim of producing data that faithfully resembles those obtained in real experiments. It allows to take into account the specificities of the bacterial genome, especially an existence of only exons and their organization in operons that are not normally present in eukaryotes.

Bacterial small RNAs (sRNAs) are regulatory elements often mentioned in the context of stress response. So are polyhydroxyalkanoates (PHAs), a possible replacement for conventional plastics, are frequently produced by bacteria facing stress conditions. PHAs then serve as the source of the carbon as well as the defense mechanism against further stress. Here, we present sRNA analysis of PHA-producing bacterium Rhodospirillum rubrum, especially the co-expression analysis of inferred sRNA candidates from RNA-Seq data. Weighted correlation network analysis (WGCNA) was used to compute clusters of genes with similar expression profiles, resulting in 28 modules. Further, the functional annotation of genes in each module was applied and the overall functional profiles were mentioned using a ‘guilt by association’ approach. Additionally, functional enrichment of modules was obtained through overrepresentation analysis (ORA). These results provide an overview of regulatory elements and their predicted functions in R. rubrum, which further unveil its dynamic properties and can help with the assessment of its industrial application.

This study compares the efficiency of Pacific Biosciences technology (PacBio) and Oxford Nanopore Technology (ONT) in sequencing, assembling, and annotating the Aneurinibacillus sp AFn2 bacterium. We aim to evaluate the performance based on contiguity, depth, and functional annotation of the resulting genome. Using ONT we generated 152,047 long reads assembling into 2 contigs with total base count of 0.4 billion which provided us efficient assembly while PacBio produced 139,701 reads, assembling into 21 contigs with a total base count of 1.4 billion. Functional annotation revealed differences in the number of coding sequences, with PacBio detecting more comprehensive gene sets than ONT. The comparative analysis done in this research shows the strengths and limitations of both the platforms, with ONT providing higher assembly contiguity and PacBio offering greater detail in genetic content. We aim to offer insights of both the sequencing technologies, guiding researchers in selecting the appropriate technology.

The complete genome sequence of thermophilic type strain Tepidimonas tawanensis LMG 22826T confirmed the previous statement of high biotechnological potential of this bacterium that is besides reported alkaline protease production capable of polyhydroxyalkanoates (PHA) synthesis. Here, we present further descriptive analysis based on pathways detection and consequently understanding of some significant properties that can be used for possible modeling purposes. In total, 108 biological pathways were detected, phaCAB operon and granule-associated proteins - phasins were found and butanoate pathway comparison with other PHA producing bacteria was provided as well as simplified PHA synthesis pathway was introduced.

The study of bacterial organisms is given great emphasis in scientific research. By studying the bacterial genome, scientists can gain knowledge of various infectious diseases. Nowadays, it is even possible to edit genes and thus advancing the field of tailored medicine by treating many genetic diseases. Furthermore, it is becoming the norm to utilize bacteria in the industry for their ability to produce important products such as plastics, or fuels. It is therefore essential to extract the necessary information about its genes and other features. This paper focuses mainly on improving the functional annotation of bacterial genomes, classification of protein-coding sequences into clusters of orthologous groups, and visualization of the final annotated genome. For this task, the python package was developed with several functions for working with the outputs of multiple annotation tools, namely eggNOG-mapper, Operon-mapper, and Batch CD-Search. The package was tested on Clostridium diolis DSM 15410 and Clostridium beijerinckii DSM 791.