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Peptide nucleic acid (PNA) clamps reduce amplification of host chloroplast and mitochondria rRNA gene sequences and increase detected diversity in 16S rRNA gene profiling analysis of oak-associated microbiota.
Environ Microbiome
January 2025
School of Natural Sciences, Bangor University, Bangor, UK.
Background: Acquiring representative bacterial 16S rRNA gene community profiles in plant microbiome studies can be challenging due to the excessive co-amplification of host chloroplast and mitochondrial rRNA gene sequences that reduce counts of plant-associated bacterial sequences. Peptide Nucleic Acid (PNA) clamps prevent this by blocking PCR primer binding or binding within the amplified region of non-target DNA to stop the function of DNA polymerase. Here, we applied a universal chloroplast (p)PNA clamp and a newly designed mitochondria (m)PNA clamp to minimise host chloroplast and mitochondria amplification in 16S rRNA gene amplicon profiles of leaf, bark and root tissue of two oak species (Quercus robur and Q.
View Article and Find Full Text PDFBarriers and facilitators to engagement with between-session work for low-intensity Cognitive Behavioural Therapy (CBT)-based interventions: a qualitative exploration of practitioner perceptions.
BMC Psychiatry
January 2025
Division of Nursing, Midwifery and Social Work, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Background: To address the growing demand for psychological treatment, healthcare providers are increasingly utilising low-intensity interventions, characterised by reduced practitioner contact and emphasis on independent patient engagement with therapeutic materials through between-session work (BSW). While BSW is critical for maximising treatment outcomes, patients and practitioners report challenges with its completion. Research identifying factors influencing between-session engagement in Cognitive Behavioural Therapy (CBT) has largely focused on high-intensity CBT, limiting understanding within low-intensity contexts.
View Article and Find Full Text PDFMetadag: a web tool to generate and analyse metabolic networks.
BMC Bioinformatics
January 2025
Mathematics and Computer Science Department, University of the Balearic Islands, Ctra Valldemossa, Km 7.5, Palma, 07122, Balearic Islands, Spain.
Background: MetaDAG is a web-based tool developed to address challenges posed by big data from omics technologies, particularly in metabolic network reconstruction and analysis. The tool is capable of constructing metabolic networks for specific organisms, sets of organisms, reactions, enzymes, or KEGG Orthology (KO) identifiers. By retrieving data from the KEGG database, MetaDAG helps users visualize and analyze complex metabolic interactions efficiently.
View Article and Find Full Text PDFFrom Farm to Community: Dispersal of Potentially Pathogenic Staphylococcus and Mammaliicoccus Species and Antimicrobial Resistance Across Shared Environments.
Curr Microbiol
January 2025
Departamento de Bioquímica e Biologia Molecular, Universidade Federal de Viçosa, Viçosa, MG, Brazil.
Staphylococcaceae are a diverse bacterial family with important implications for human and animal health. This study highlights the One Health relevance of their environmental dispersal, particularly, by identifying closely related or genetically identical strains circulating between farm and community environments. Environmental Staphylococcaceae strains were isolated from animal farms and interconnected areas within a university setting, both influenced by anthropogenic activities.
View Article and Find Full Text PDFFunctional innovation through new genes as a general evolutionary process.
Nat Genet
January 2025
Department of Ecology and Evolution, The University of Chicago, Chicago, IL, USA.
In the past decade, our understanding of how new genes originate in diverse organisms has advanced substantially, and more than a dozen molecular mechanisms for generating initial gene structures were identified, in addition to gene duplication. These new genes have been found to integrate into and modify pre-existing gene networks primarily through mutation and selection, revealing new patterns and rules with stable origination rates across various organisms. This progress has challenged the prevailing belief that new proteins evolve from pre-existing genes, as new genes may arise de novo from noncoding DNA sequences in many organisms, with high rates observed in flowering plants.
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