Browsing by Subject "Phylogenetic analysis"
Now showing items 1-7 of 7
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(2022)Background: SARS-CoV-2 is the highly transmissible etiologic agent of coronavirus disease 2019 (COVID-19) and has become a global scientific and public health challenge since December 2019. Several new variants of SARS-CoV-2 have emerged globally raising concern about prevention and treatment of COVID-19. Early detection and in-depth analysis of the emerging variants allowing pre-emptive alert and mitigation efforts are thus of paramount importance. Results: Here we present ClusTRace, a novel bioinformatic pipeline for a fast and scalable analysis of sequence clusters or clades in large viral phylogenies. ClusTRace offers several high-level functionalities including lineage assignment, outlier filtering, aligning, phylogenetic tree reconstruction, cluster extraction, variant calling, visualization and reporting. ClusTRace was developed as an aid for COVID-19 transmission chain tracing in Finland with the main emphasis on fast screening of phylogenies for markers of super-spreading events and other features of concern, such as high rates of cluster growth and/or accumulation of novel mutations. Conclusions: ClusTRace provides an effective interface that can significantly cut down learning and operating costs related to complex bioinformatic analysis of large viral sequence sets and phylogenies. All code is freely available from https://bitbucket.org/plyusnin/clustrace/
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(BioMed Central, 2016)Abstract Feruloyl esterases (FAEs) represent a diverse group of carboxyl esterases that specifically catalyze the hydrolysis of ester bonds between ferulic (hydroxycinnamic) acid and plant cell wall polysaccharides. Therefore, FAEs act as accessory enzymes to assist xylanolytic and pectinolytic enzymes in gaining access to their site of action during biomass conversion. Their ability to release ferulic acid and other hydroxycinnamic acids from plant biomass makes FAEs potential biocatalysts in a wide variety of applications such as in biofuel, food and feed, pulp and paper, cosmetics, and pharmaceutical industries. This review provides an updated overview of the knowledge on fungal FAEs, in particular describing their role in plant biomass degradation, diversity of their biochemical properties and substrate specificities, their regulation and conditions needed for their induction. Furthermore, the discovery of new FAEs using genome mining and phylogenetic analysis of current publicly accessible fungal genomes will also be presented. This has led to a new subfamily classification of fungal FAEs that takes into account both phylogeny and substrate specificity.
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(2021)Background Akkermansia muciniphila is a member of the human gut microbiota where it resides in the mucus layer and uses mucin as the sole carbon, nitrogen and energy source. A. muciniphila is the only representative of the Verrucomicrobia phylum in the human gut. However, A. muciniphila 16S rRNA gene sequences have also been found in the intestines of many vertebrates. Results We detected A. muciniphila-like bacteria in the intestines of animals belonging to 15 out of 16 mammalian orders. In addition, other species belonging to the Verrucomicrobia phylum were detected in fecal samples. We isolated 10 new A. muciniphila strains from the feces of chimpanzee, siamang, mouse, pig, reindeer, horse and elephant. The physiology and genome of these strains were highly similar in comparison to the type strain A. muciniphila Muc(T). Overall, the genomes of the new strains showed high average nucleotide identity (93.9 to 99.7%). In these genomes, we detected considerable conservation of at least 75 of the 78 mucin degradation genes that were previously detected in the genome of the type strain Muc(T). Conclusions The low genomic divergence observed in the new strains may indicate that A. muciniphila favors mucosal colonization independent of the differences in hosts. In addition, the conserved mucus degradation capability points towards a similar beneficial role of the new strains in regulating host metabolic health.
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(Helsingin yliopisto, 2021)Lipoxygenase enzymes, which contribute significantly to storage protein in legume seeds have been reported to cause the emission of volatile compounds associated with the generation of off-flavours. This is an are important factor limiting the acceptance of faba bean (Vicia faba) I foods. This study aimed at using bioinformatic tools to identify seed-borne lipoxygenase (LOX) genes and to design a biological tool using molecular techniques to find changes in sequence in faba bean lines. LOX gene mining by Exonerate sequence comparison on the whole genome sequence of faba bean was used to identify six LOX genes containing Polycystin-1, Lipoxygenase, Alpha-Toxin (PLAT) and/or LH2 LOX domains. Their sequence properties, evolutionary relationships, important conserved LOX motifs and subcellular location were analysed. The LOX gene proteins identified contained 272 – 853 amino acids (aa). The molecular weight ranged from 23.67 kDa in Gene 6 to 96.45 kDA in Gene 1. All the proteins had isoelectric points in the acidic range except Genes 6 and 7 which were alkaline. Only one gene had both LOX conserved domains with aa sequence length similar with that found in soybean and pea LOX genes and isoelectric properties with soybean LOX3. Phylogenetic analysis indicated that the genes were clustered into 9S LOX and 13S LOX types alongside other seed LOX genes in some legumes. Five motifs were found, and sequence analysis showed that three genes (Gene 1, 2 and 3) contained the 38-aa residue motif that includes five histidine residues [His-(X)4-His-(X)4-His-(X)17-His-(X)8-His]. The subcellular localization of the lipoxygenase proteins was predicted to be primarily the cytoplasm and chloroplast. Primers covering ~1.2 kb were designed, based on the conserved region of Genes 1, 2 and 3 nucleotide sequences. Gel electrophoresis showed the PCR amplification of the seed LOX gene at the expected region for twelve faba bean lines. Phylogenetic analysis showed evolutionary divergence among faba bean lines for sequenced and amplified region of their respective seed LOX alleles.
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(2023)Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, sampling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several diverse bacterial genome data sets representing major human pathogens.
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(2013)Background: Swine influenza is an infectious acute respiratory disease of pigs caused by influenza A virus. We investigated the time of entry of swine influenza into the Finnish pig population. We also describe the molecular detection of two types of influenza A (H1N1) viruses in porcine samples submitted in 2009 and 2010. This retrospective study was based on three categories of samples: blood samples collected for disease monitoring from pigs at major slaughterhouses from 2007 to 2009; blood samples from pigs in farms with a special health status taken in 2008 and 2009; and diagnostic blood samples from pigs in farms with clinical signs of respiratory disease in 2008 and 2009. The blood samples were tested for influenza A antibodies with an antibody ELISA. Positive samples were further analyzed for H1N1, H3N2, and H1N2 antibodies with a hemagglutination inhibition test. Diagnostic samples for virus detection were subjected to influenza A M-gene-specific real-time RT-PCR and to pandemic influenza A H1N1-specific real-time RT-PCR. Positive samples were further analyzed with RT-PCRs designed for this purpose, and the PCR products were sequenced and sequences analyzed phylogenetically. Results: In the blood samples from pigs in special health class farms producing replacement animals and in diagnostic blood samples, the first serologically positive samples originated from the period July–August 2008. In samples collected for disease monitoring, < 0.1%, 0% and 16% were positive for antibodies against influenza A H1N1 in the HI test in 2007, 2008, and 2009, respectively. Swine influenza A virus of avian-like H1N1 was first detected in diagnostic samples in February 2009. In 2009 and 2010, the avian-like H1N1 virus was detected on 12 and two farms, respectively. The pandemic H1N1 virus (A(H1N1) pdm09) was detected on one pig farm in 2009 and on two farms in 2010. Conclusions: Based on our study, swine influenza of avian-like H1N1 virus was introduced into the Finnish pig population in 2008 and A(H1N1)pdm09 virus in 2009. The source of avian-like H1N1 infection could not be determined. Cases of pandemic H1N1 in pigs coincided with the period when the A(H1N1)pdm09 virus was spread in humans in Finland.
