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Biology subjects

Huws, S.

Publications and source records attributed to Huws, S..

3 recordsLinked to original sources

Microbiomes attached to fresh perennial ryegrass- are temporally resilient and adapt to changing ecological niches

Gut microbiomes, such as the rumen, greatly influence host nutrition due to their feed energy-harvesting capacity. We investigated temporal ecological interactions facilitating energy-harvesting at the fresh perennial ryegrass (PRG)-biofilm interface in the rumen using an in sacco approach and prokaryotic metatranscriptomic profiling. Network analysis identified two distinct sub-microbiomes primarily representing primary ([≤]4h) and secondary ([≥]4h) colonisation phases and the most transcriptionally active bacterial families (i.e Fibrobacteriaceae, Selemondaceae and Methanobacteriaceae) did not interact with either sub-microbiome, indicating non-cooperative behaviour. Conversely, Prevotellaceae had most transcriptional activity within the primary sub-microbiome (focussed on protein metabolism) and Lachnospiraceae within the secondary sub-microbiome (focussed on carbohydrate degradation). Putative keystone taxa, with low transcriptional activity, were identified within both sub-microbiomes, highlighting the important synergistic role of minor bacterial families, however, we hypothesise that they may be cheating in order to capitalise on the energy-harvesting capacity of other microbes. In terms of chemical cues underlying transition from primary to secondary colonisation phases, we suggest that AI-2 based quorum sensing plays a role, based on LuxS gene expression data, coupled with changes in PRG chemistry. In summary, this study provides the first major insight into the complex temporal ecological interactions occurring at the plant-biofilm interface within the rumen.

microbiology↗

BioSAXS measurements reveal that two antimicrobial peptides induce similar molecular changes in Gram-negative and Gram-positive bacteria

Two highly active short broad-spectrum AMPs (14D and 69D) with unknown mode of action have been investigated in regards to their effect against the Gram-negative bacteria E. coli and the Gram-positive bacteria methicillin-resistant Staphylococcus aureus (MRSA). Minimal inhibitory concentration (MIC) measurements using a cell density of 108 cfu/ml resulted in values between 16 and 32 g/ml. Time kill experiments using 108 cfu/ml revealed complete killing, except for 69D in combination with MRSA, where bacterial load was reduced a million times. Small angle X-ray scattering of biological samples (BioSAXS) at 108 cfu/ml was applied to investigate the ultrastructural changes in E. coli and MRSA in response to these two broad-spectrum AMPs. In addition, electron microscopy (EM) was performed to visualize the treated and non-treated bacteria. As expected, the scattering curves generated using BioSAXS show the ultrastructure of the Gram-positive and Gram-negative bacteria to be very different (BioSAXS is not susceptible to the outer shape). After treatment with either peptide, the scattering curves of E. coli and MRSA cells are much more alike. This data in conjunction with the EM indicates that ribosomes might be effected by the treatment as well as changes in the nucleoid occurs. Whereas in EM it is notoriously difficult to observe changes for spherical Gram-positives, the BioSAXS results are superior and reveal strongly similar effects for both peptides induced in Gram-positive as well as Gram-negative bacteria. Given the high-throughput possibility and robust statistics BioSAXS can support and speed up mode of action research in AMPs and other antimicrobial compounds, making a contribution towards the development of urgently needed drugs against resistant bacteria.

biophysics↗

Computational haplotype recovery and long-read validation identifies novel isoforms of industrially relevant enzymes from natural microbial communities

Elucidation of population-level diversity of microbiomes is a significant step towards a complete understanding of the evolutionary, ecological and functional importance of microbial communities. Characterizing this diversity requires the recovery of the exact DNA sequence (haplotype) of each gene isoform from every individual present in the community. To address this, we present Hansel and Gretel: a freely-available data structure and algorithm, providing a software package that reconstructs the most likely haplotypes from metagenomes. We demonstrate recovery of haplotypes from short-read Illumina data for a bovine rumen microbiome, and verify our predictions are 100% accurate with long-read PacBio CCS sequencing. We show that Gretels haplotypes can be analyzed to determine a significant difference in mutation rates between core and accessory gene families in an ovine rumen microbiome. All tools, documentation and data for evaluation are open source and available via our repository: https://github.com/samstudio8/gretel

bioinformatics↗