HEДокторантска мрежа2026–2029

StraDiVarious · Doctoral Network on Strains, Diagnostics and Variants

„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“

Период
2026-01-01 → 2029-12-31
Финансиране от ЕС
4 799 002 €
Участници
15
Схема
HORIZON-TMA-MSCA-DN

Линиите свързват координатора с партньорите.

Накратко на български

Повърхностните протеини (адхезини) на опасни бактерии като S. aureus се анализират, за да се разбере как те се закрепят към човешките клетки. Това помага за създаването на по-бързи диагностични тестове и нови методи за борба с бактериите, устойчиви на антибиотици.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Цел на проекта

Resistance to antibiotic treatment of bacterial infections is a major threat to human health worldwide, with last-resort antibiotics becoming ineffective. Bacteria like carbapenem-resistant Acinetobacter baumannii, Enterobacterales and Pseudomonas aeruginosa head the WHO global pathogen priority list. New strategies are needed to treat AMR bacteria.Our DN StraDiVarious proposes targeting a key virulence trait: the initial interaction of bacteria with the host. Adhesion is the first and decisive step in infection, mediated by surface proteins called ‘adhesins’, which interact, either directly or indirectly, with the host cell surface to manipulate the host response. Our hypothesis is that we can distinguish between less virulent and more virulent strains of bacteria based on the fine details of their adhesins. This makes the adhesins interesting targets for both diagnostics and therapeutics. The StraDiVarious intersectoral network (including large Pharma and SMEs) will train the next generation of researchers in this important area, focusing on the initial interaction. Our targets include the clinically most relevant pathogens from the “ESKAPE” group (eg. A. baumannii, K. pneumoniae, P. aeruginosa, E. cloacae and S. aureus). The DCs will use state-of-the-art techniques at different levels: infection (tissue/cell), biochemical interactions (cell/molecule), structure (molecule/atom) and timescale (dynamics). We will integrate this information with large clinical strain data (genomics/ proteomics) and use machine-learning to understand the cause of virulence/non-virulence at the level of individual bacterial strains and protein variants. This information will be used not only to develop next-generation strain-specific rapid diagnostics suitable for point-of-care applications but also for finding potential drug/vaccine targets. Such precision medicine will reduce load on the health-care system, avert the antibiotic crisis, and improve patient quality of life.

Оригинален текст от CORDIS (на английски).

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Данни: CORDIS, © Европейски съюз