TY - JOUR

T1 - Moving towards improved surveillance and earlier diagnosis of aquatic pathogens: from traditional methods to emerging technologies

AU - MacAulay, Scott

AU - Ellison, Amy

AU - Kille, Peter

AU - Cable, Jo

N1 - Biotechnology and Biological Sciences Research Council. Grant Number: BB/T008741/1

PY - 2022/9

Y1 - 2022/9

N2 - Early and accurate diagnosis is key to mitigating the impact of infectious diseases, along with efficient surveillance. This however is particularly challenging in aquatic environments due to hidden biodiversity and physical constraints. Traditional diagnostics, such as visual diagnosis and histopathology, are still widely used, but increasingly technological advances such as portable Next Generation Sequencing (NGS) and Artificial Intelligence (AI) are being tested for early diagnosis. The most straightforward methodologies, based on visual diagnosis, rely on specialist knowledge and experience but provide a foundation for surveillance. Future computational remote sensing methods, such as AI image diagnosis and drone surveillance, will ultimately reduce labour costs whilst not compromising on sensitivity, but they require capital and infrastructural investment. Molecular techniques have advanced rapidly in the last 30 years, from standard PCR through loop-mediated isothermal amplification (LAMP) to NGS approaches, providing a range of technologies that support the currently popular eDNA diagnosis. There is now vast potential for transformative change driven by developments in human diagnostics. Here we compare current surveillance and diagnostic technologies with those that could be used or developed for use in the aquatic environment, against three gold standard ideals of high sensitivity, specificity, rapid diagnosis, and cost-effectiveness.

AB - Early and accurate diagnosis is key to mitigating the impact of infectious diseases, along with efficient surveillance. This however is particularly challenging in aquatic environments due to hidden biodiversity and physical constraints. Traditional diagnostics, such as visual diagnosis and histopathology, are still widely used, but increasingly technological advances such as portable Next Generation Sequencing (NGS) and Artificial Intelligence (AI) are being tested for early diagnosis. The most straightforward methodologies, based on visual diagnosis, rely on specialist knowledge and experience but provide a foundation for surveillance. Future computational remote sensing methods, such as AI image diagnosis and drone surveillance, will ultimately reduce labour costs whilst not compromising on sensitivity, but they require capital and infrastructural investment. Molecular techniques have advanced rapidly in the last 30 years, from standard PCR through loop-mediated isothermal amplification (LAMP) to NGS approaches, providing a range of technologies that support the currently popular eDNA diagnosis. There is now vast potential for transformative change driven by developments in human diagnostics. Here we compare current surveillance and diagnostic technologies with those that could be used or developed for use in the aquatic environment, against three gold standard ideals of high sensitivity, specificity, rapid diagnosis, and cost-effectiveness.

KW - aquatic diagnostics

KW - aquatic disease

KW - disease surveillance

KW - eDNA

KW - molecular diagnostics

KW - visual diagnosis

U2 - 10.1111/raq.12674

DO - 10.1111/raq.12674

M3 - Review article

VL - 14

SP - 1813

EP - 1829

JO - Reviews in Aquaculture

JF - Reviews in Aquaculture

SN - 1753-5123

IS - 4

ER -