Biology subjects

Berkeley, M.

Publications and source records attributed to Berkeley, M..

3 recordsLinked to original sources

bioRxiv2025

Evolution of T cell responses in the tuberculin skin test reveals generalisable Mtb-reactive T cell metaclones.

T cells contribute to immune protection and pathogenesis in tuberculosis, but measurements of polyclonal responses have failed to resolve correlates of outcome. We report the first temporal evaluation of the human in vivo clonal repertoire of Mtb-reactive T cell responses, by T cell receptor (TCR) sequencing at the site of a standardised antigenic challenge. Initial recruitment of non-Mtb reactive T cells is followed by enrichment of Mtb-reactive clones arising from oligoclonal T cell proliferation. We introduce a modular computational pipeline, Metaclonotypist, to sensitively cluster distinct TCRs with shared epitope specificity, which we apply here to establish a catalogue of public Mtb-reactive HLA-restricted T cell metaclones. Although most in vivo Mtb-reactive T cells are private, 10 metaclones were sufficient to identify Mtb-T cell reactivity across our study population (N[≥]128), indicating striking population level immunodominance of specific TCR-peptide interactions that may offer novel approaches to patient stratification and vaccine development.

immunology↗

bioRxiv2025

LEMMIv2: Benchmarking Framework for Metagenomic and 16S Amplicon Profilers with a Catalogue of Evaluated Tools.

Sequencing has transformed microbial studies, enabling metagenomic analysis of microbial communities without the need for culturing or prior knowledge of sample composition. The essential analysis of the primary sequencing reads, however, is complex and led to the development of diverse computational strategies. The plethora of available methods and their numerous parameters poses a practical challenge for practitioners and creates a visibility barrier for developers of novel approaches. In addition to technical limitations related to user computing environment, algorithmic solutions, and their scalability, there are critical considerations regarding the reference database, i.e. the knowledge against which the data is interpreted, as well as the target of the analysis, expected sample composition, and peculiarities of read data from different sequencing platforms. To facilitate informed decision-making, we introduced the LEMMI platform for continuous benchmarking of software tools for metagenomic analyses, where developers can receive impartial benchmarks for method publication and users benefit from a standardized and benchmarked catalogue of tools. Here we present developments of LEMMI version 2, including assessments of different target scenarios, long- and short-read sequencing data, alternative taxonomies, and a standalone pipeline (https://lemmi.ezlab.org). In addition to LEMMI, which focuses on shotgun metagenomic profiling, we extended this approach to bacteria profiling with 16S amplicon sequencing (https://lemmi16S.ezlab.org).

genomics↗

bioRxiv2017

Cross-Site Comparison of Ribosomal Depletion Kits for Illumina RNAseq Library Construction

Ribosomal RNA (rRNA) comprises at least 90% of total RNA extracted from mammalian tissue or cell line samples. Informative transcriptional profiling using massively parallel sequencing technologies requires either enrichment of mature poly-adenylated transcripts or targeted depletion of the rRNA fraction. The latter method is of particular interest because it is compatible with degraded samples such as those extracted from FFPE and also captures transcripts that are not poly-adenylated such as some non-coding RNAs. Here we provide a cross-site study that evaluates the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples. We find that all of the kits are capable of performing significant ribosomal depletion, though there are differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify [~]14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes between kits suggests that transcript length may be a key factor in library production efficiency. These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them.

genomics↗