Isolation, identification, and biological characteristics of Clostridium sartagoforme from rabbit

In order to develop microbial additives for rabbit feed, a spore-forming bacteria was isolated from the feces of Hyla rabbit using reinforced clostridium medium (RCM). The 16S rDNA sequence of the bacterium was subjected to pairwise sequence alignment using BLAST; the colony morphology, and physiological, biochemical, and stress resistance were studied. The results showed that the bacterium was Clostridium sartagoforme, a gram positive anaerobe, which can produce spores. The colony diameter was 0.5 mm—2.5 mm, the diameter of the bacteria was 0.5 μm—1.0 μm × 2.0 μm—6.3 μm, and the spore diameter was 1 μm—1.2 μm × 1 μm—1.2 μm. C. sartagoforme can utilize various sugars and alcohols such as fructose, galactose, sorbitol, and inositol. It secreted cellulase into the extracellular environment to form a transparent hydrolysis circle in Congo red medium, it could not liquify gelatin, and the lysine decarboxylase reaction was positive. In liquid medium it entered the stable growth period after 9 h of inoculation. Additionally, it had good stress resistance with a survival rate that exceeded 53% after gastric juice (pH 2.5) treatment for 3 h, it grew in a medium with a bile salt concentration of 0.3%, and the survival rate exceeded 85% after 10 minutes at 80°C. Moreover, animal testing indicated that this strain has no adverse effects on the morbidity and mortality of rabbits. In summary, C. sartagoforme XN-T4 was isolated from rabbit feces. This bacterium has good resistance to stress, can decompose a variety of monosaccharides and polysaccharides including cellulose, which is relatively harmless for animal health.

Block aligner: fast and flexible pairwise sequence alignment with SIMD-accelerated adaptive blocks

Background: The Smith-Waterman-Gotoh alignment algorithm is the most popular method for comparing biological sequences. Recently, Single Instruction Multiple Data methods have been used to speed up alignment. However, these algorithms have limitations like being optimized for specific scoring schemes, cannot handle large gaps, or require quadratic time computation. Results: We propose a new algorithm called block aligner for aligning nucleotide and protein sequences. It greedily shifts and grows a block of computed scores to span large gaps within the aligned sequences. This greedy approach is able to only compute a fraction of the DP matrix. In exchange for these features, there is no guarantee that the computed scores are accurate compared to full DP. However, in our experiments, we show that block aligner performs accurately on various realistic datasets, and it is up to 9 times faster than the popular Farrar's algorithm for protein global alignments. Conclusions: Our algorithm has applications in computing global alignments and X-drop alignments on proteins and long reads. It is available as a Rust library at https://github.com/Daniel-Liu-c0deb0t/block-aligner.

HyperEx: A Tool to Extract Hypervariable Regions from 16S rRNA Sequencing Data

The 16S ribosomal RNA gene is one of the most studied genes in biology. This 16S ribosomal RNA importance is due to its wide application in phylogenetics and taxonomic elucidation of bacteria and archaea. Indeed, 16S ribosomal RNA is present in almost all bacteria and archaea and has, among many other useful characteristics, a low mutation rate. The 16S ribosomal RNA is composed of nine hypervariable regions which are commonly targeted by high throughput sequencing technologies in identification or community studies like metabarcoding studies. Unfortunately, the hypervariable regions do not have the same taxonomic resolution among all bacteria taxa. This requires a preliminary in silico analysis to determine the best hypervariable regions to target in a particular study. Nevertheless, to the best of our knowledge, no automated primer-based open-source tool exists to extract hypervariable regions from complete or near-complete 16S rRNA sequencing data. Here we present HyperEx which efficiently extracts the hypervariable region of interest based on embedded primers or user-given primers. HyperEx implements the Myers algorithm for the exact pairwise sequence alignment. HyperEx is freely available under the MIT license as an operating system independent Rust command-line tool at https://github.com/Ebedthan/hyperex and https://crates.io.

Accelerating long-read analysis on modern CPUs

Long read sequencing is now routinely used at scale for genomics and transcriptomics applications. Mapping of long reads or a draft genome assembly to a reference sequence is often one of the most time consuming steps in these applications. Here, we present techniques to accelerate minimap2, a widely used software for mapping. We present multiple optimizations using SIMD parallelization, efficient cache utilization and a learned index data structure to accelerate its three main computational modules, i.e., seeding, chaining and pairwise sequence alignment. These result in reduction of end-to-end mapping time of minimap2 by up to 3.5x while maintaining identical output.

Refining pairwise sequence alignments of membrane proteins by the incorporation of anchors

The alignment of primary sequences is a fundamental step in the analysis of protein structure, function, and evolution, and in the generation of homology-based models. Integral membrane proteins pose a significant challenge for such sequence alignment approaches, because their evolutionary relationships can be very remote, and because a high content of hydrophobic amino acids reduces their complexity. Frequently, biochemical or biophysical data is available that informs the optimum alignment, for example, indicating specific positions that share common functional or structural roles. Currently, if those positions are not correctly matched by a standard pairwise sequence alignment procedure, the incorporation of such information into the alignment is typically addressed in an ad hoc manner, with manual adjustments. However, such modifications are problematic because they reduce the robustness and reproducibility of the aligned regions either side of the newly matched positions. Previous studies have introduced restraints as a means to impose the matching of positions during sequence alignments, originally in the context of genome assembly. Here we introduce position restraints, or “anchors” as a feature in our alignment tool AlignMe, providing an aid to pairwise global sequence alignment of alpha-helical membrane proteins. Applying this approach to realistic scenarios involving distantly-related and low complexity sequences, we illustrate how the addition of anchors can be used to modify alignments, while still maintaining the reproducibility and rigor of the rest of the alignment. Anchored alignments can be generated using the online version of AlignMe available at www.bioinfo.mpg.de/AlignMe/.

Molecular Identification of Five Multidrug-resistant Salmonella Enterica Serovars Isolated from Egyptian Poultry Farms

Salmonella spp is the main cause of foodborne salmonellosis that is considered a public health threat all over the world. The robust usage of antibiotics in Egyptian poultry farms resulted in increasing the prevalence of multi-drug resistant Salmonella enterica. In this study, the authors identify five multi-drug resistant Salmonella enterica serovars. Multidrug-resistant characteristics of these isolates were detected. The taxonomic evidence of these isolates was investigated based on 16S rRNA gene sequence and pairwise sequence alignment between the isolates' sequence and the nearest sequences in the database. In silico restriction maps and phylogenetic trees were also constructed. The obtained sequences were deposited in the database under accession numbers MW311328.1, MW311371.1, MN820824.1, MN822653.1 and MW310702.1 for Salmonella enterica subsp. enterica serovar Enteritidis strains EG.SmE1, EG.SmE2 and Salmonella enterica subsp. enterica serovar Typhimurium strains EG.SmT1, EG.SmT2, EG.SmT3, respectively. The five Salmonella isolates in this study showed multi-drug resistant characteristics. Salmonella Typhimurium isolate EG.SmT3 revealed resistance to more than five antibiotics. Results of pairwise sequence alignment, restriction maps and phylogenetic tree confirmed the close relationship between S. enteritidis isolates (EG.SmE1, EG. SmE2) and S. typhimurium isolates (EG.SmT1, EG.SmT2). However, the other S. typhimurium isolate (EG.SmT3) revealed the lowest identity ratio (98.6%) with the nearest sequence. The relative divergence of this isolate could be attributed to proposed mutations as a result of the vigorous use of antibiotics in Egyptian poultry farms.

Efficient Multiple Sequences Alignment Algorithm Generation via Components Assembly Under PAR Framework

As a key algorithm in bioinformatics, sequence alignment algorithm is widely used in sequence similarity analysis and genome sequence database search. Existing research focuses mainly on the specific steps of the algorithm or is for specific problems, lack of high-level abstract domain algorithm framework. Multiple sequence alignment algorithms are more complex, redundant, and difficult to understand, and it is not easy for users to select the appropriate algorithm; some computing errors may occur. Based on our constructed pairwise sequence alignment algorithm component library and the convenient software platform PAR, a few expansion domain components are developed for multiple sequence alignment application domain, and specific multiple sequence alignment algorithm can be designed, and its corresponding program, i.e., C++/Java/Python program, can be generated efficiently and thus enables the improvement of the development efficiency of complex algorithms, as well as accuracy of sequence alignment calculation. A star alignment algorithm is designed and generated to demonstrate the development process.