m+Medelevator.RU
← Поиск публикаций
Tuberculosis (Edinburgh, Scotland) · 2024

Assessment of transcriptional markers for the differentiation of Mycobacterium mungi infection status in free-ranging banded mongoose (Mungos mungo).

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Sybertz Nicholas M, Al Jubaer Shamim, Larsen Michelle H, Alexander Kathleen A

Аннотация

There is an increasingly urgent need to improve our ability to accurately forecast and control zoonotic diseases in wildlife reservoirs. We are confronted, however, with the continued challenge of accurately determining host infection status across space and time. This dilemma is epitomized with the Mycobacterium tuberculosis Complex (MTBC) pathogens and particularly in free-ranging wildlife, a critical global challenge for both human and animal health. In humans, transcriptional markers have been increasingly identified as a robust tool for diagnosing Mycobacterium tuberculosis (MTB) infection status but have rarely been utilized for diagnosing TB in free-ranging wildlife populations. Here, we report the first use of transcriptional markers to evaluate TB infection status in a free-ranging wildlife species, banded mongoose (Mungos mungo), infected with the MTBC pathogen, Mycobacterium mungi. In this study, we found that GBP5 and DUSP3 were significantly upregulated in free-ranging banded mongoose infected with M. mungi. These results provide the first step in developing an antemortem diagnostic tool for use in free-ranging wildlife species. Our results highlight the potential of transcriptional marker-based assays to advance our ability to detect and manage TB in free-ranging wildlife, especially in field studies and other scenarios when conventional diagnostics are not feasible.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты