Biology subjects

Meyer, D. F.

Publications and source records attributed to Meyer, D. F..

3 recordsLinked to original sources

bioRxiv2026

Toward closing a heartwater monitoring gap with a new pan-species ELISA suitable for domestic ruminants, wildlife, and camels.

Heartwater, caused by the tick-borne bacterium Ehrlichia ruminantium, threatens ruminant production in sub-Saharan Africa and the Caribbean. Serological surveillance relies on species-specific ELISAs, so wildlife and camelids, which are potential reservoirs or sentinels, have no validated tools. We developed and evaluated a pan-species indirect ELISA prototype (ID Screen Ehrlichia ruminantium Indirect Multi-species, Innovative Diagnostics) that detects anti-MAP1-B antibodies in all mammals. A positivity threshold of 30% relative positivity percentage (RPP) was empirically established from 707 heartwater-negative cattle, goat and sheep sera from three regions (maximum RPP 22.1%). Against a goat-specific reference ELISA (n = 503), the prototype showed 98.2% sensitivity, 97.2% specificity and 97.6% overall agreement. ROC analysis identified a Youden-optimal cut-off of 29.96%, confirming the empirical threshold. Inter-assay reproducibility was satisfactory (mean CV 7.4%), and qualitative classification remained stable across runs, including for a near-threshold sample. In four vaccinated sheep, the prototype detected seroconversion at the same time points as a sheep-specific ELISA. In non-domestic hosts, the assay gave uniformly low RPP values in 24 zoo animals of ten species from a heartwater-free area. By contrast, 4.5% of 111 dromedary camels from Chad exceeded the threshold. Eight wildlife species from Kruger National Park (n = 405) were tested and five species presented high median RPP values. This single-protocol assay provides a reproducible tool for integrated heartwater surveillance across livestock, camelids and wildlife, in Africa, in the Caribbean and in all countries threatened by the emergence of heartwater.

microbiology↗

bioRxiv2026

HInt: interaction-based homology discovery through accelerated genome-scale AlphaFold screening

Identifying homologous proteins across deep evolutionary distances remains a major challenge because sequence and structural similarity progressively become undetectable over time. Although protein-protein interactions (PPIs) are often constrained by function and evolution, whether conserved interaction interfaces can provide an independent signal for homology detection has remained largely unexplored owing to the computational cost of proteome-scale interaction prediction. Here we introduce HInt (Homology by Interaction), an accelerated AlphaFold-based framework that enables practical proteome-scale PPI prediction through biologically informed pre-filtering and optimised high-throughput structure modelling. Using HInt, we establish interaction-based similarity as a third axis of homology detection. We show that conserved interaction interfaces reveal homologous relationships that remain inaccessible to conventional sequence- and structure-based approaches. Application of HInt to both prokaryotic and eukaryotic systems, together with experimental validation, uncovered a previously unrecognised VirB5 pilus-tip protein in the F-plasmid type IV secretion system and a previously unannotated F-box-like protein in the Saccharomyces cerevisiae ubiquitin-proteasome system. By enabling practical proteome-scale interaction screening, HInt provides a general framework for uncovering hidden homologues and expands the conceptual landscape of protein homology inference.

molecular biology↗

bioRxiv2018

Searching Algorithm for Type IV Effector proteins (S4TE) 2.0: improved tools for type IV effector prediction, analysis and comparison

Bacterial pathogens have evolved numerous strategies to corrupt, hijack or mimic cellular processes in order to survive and proliferate. Among those strategies, Type IV effectors (T4Es) are proteins secreted by pathogenic bacteria to manipulate host cell processes during infection. They are delivered into eukaryotic cells in an ATP-dependent manner via the type IV secretion system, a specialized multiprotein complex. T4Es contain a wide spectrum of features including eukaryotic-like domains, localization signals or a C-terminal translocation signal. A combination of these features enables prediction of T4Es in a given bacterial genome. In this study, we developed a web-based comprehensive suite of tools with a user-friendly graphical interface. This version 2.0 of S4TE (Searching Algorithm for Type IV Effector Proteins; http://sate.cirad.fr) enables accurate prediction and comparison of T4Es. Search parameters and threshold can be customized by the user to work with any genome sequence, whether publicly available or not. Applications range from characterizing effector features and identifying potential T4Es to analyzing the effectors based on the genome G+C composition and local gene density. S4TE 2.0 allows the comparison of putative T4E repertoires of up to four bacterial strains at the same time. The software identifies T4E orthologs among strains and provides a Venn diagram and lists of genes for each intersection. New interactive features offer the best visualization of the location of candidate T4Es and hyperlinks to NCBI and Pfam databases. S4TE 2.0 is designed to evolve rapidly with the publication of new experimentally validated T4Es, which will reinforce the predictive power of the algorithm. The computational methodology can be used to identify a wide spectrum of candidate bacterial effectors that lack sequence conservation but have similar amino acid characteristics. This approach will provide very valuable information about bacterial host-specificity and virulence factors, and help identify host targets for the development of new anti-bacterial molecules.

bioinformatics↗