Developing liquid AP-MALDI MS as a rapid large-scale classification method for determining farm animal health

开发液体 AP-MALDI MS 作为确定农场动物健康的快速大规模分类方法

基本信息

批准号：
BB/R002975/1
负责人：
Rainer Cramer
金额：
$ 36.07万
依托单位：
University of Reading
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FR002975%2F1
关键词：
Developing liquid AP MALDI MS

项目摘要

Good farm animal health is paramount for food safety and security. It also reduces the burden on the environment and public health by a reduction in disease treatments using antimicrobials or other drugs. Greater knowledge and earlier detection of agriculturally important diseases will result in better farm disease management and welfare of farm animals as well as improved food produce yield and safety. In addition, recent food adulteration scandals have highlighted the need for faster and more detailed knowledge of our food and its production line to determine and guarantee food authenticity.Information gathering for all of the above is still limited by the analytical methods available. Some of these are not sufficiently cost-effective and/or too cumbersome and slow for rapid action. Others can be fast but are often very targeted, allowing the detection of only one condition, and limited in their practical use, particularly in combination with other tests.Fortunately, advances in modern mass spectrometry now allow highly sensitive recordings of the molecular profiles of biological samples such as milk. In combination with advanced bioinformatics these recordings can be used to teach computer algorithms for future classification and thus detection of agriculturally important conditions such as mastitis. As modern mass spectrometry is one of the most sensitive molecular detection and characterisation techniques, allowing the analysis of many molecular biomarkers simultaneously, there is now a great opportunity to make a step change in the early detection of such markers for many diseases in a cost-effective and fast way.However, cost-effectiveness and speed of analysis can still be limited due to the sample preparation necessary for analysis by mass spectrometry. Our lab has recently demonstrated that biological samples such as milk can be effectively analysed by mass spectrometry with no or minimal sample preparation by using liquid MALDI mass spectrometry.In collaboration with the University of Reading's Department of Agriculture and Centre of Dairy Research (CEDAR) with its large research herd of around 600 cows, we now aim to explore and fully develop a rapid analysis workflow for biological fluids from farm animals based on modern liquid MALDI mass spectrometry. This workflow should allow for early and specific detection of agriculturally important diseases and conditions, exploiting to the fullest mass spectrometry's great potential in highly sensitive, fast and inexpensive characterisation of the health of our farm animals and their produce.

良好的农场动物健康对食品安全和保障至关重要。它还通过使用抗菌药物或其他药物减少疾病治疗方法来减轻环境和公共卫生的负担。更大的知识和早期发现农业重要疾病将导致更好的农场疾病管理和农场动物的福利以及改善的粮食产量和安全性。此外，最近的食品掺假丑闻强调了对我们的食物及其生产线更快，更详细的了解，以确定和保证食品真实性。上述所有内容的信息收集仍然受到可用的分析方法的限制。其中一些不是足够的成本效益和/或过于繁琐的，并且无法进行快速行动。其他人可以很快，但通常是非常有针对性的，只能检测到一种情况，并且在实际使用方面有限，尤其是与其他测试结合使用。结合先进的生物信息学，这些录音可用于教授计算机算法以进行未来分类，从而检测农业重要的疾病，例如乳腺炎。由于现代质谱法是最敏感的分子检测和表征技术之一，因此可以同时分析许多分子生物标志物，因此现在有一个很好的机会在早期发现这些疾病的早期检测中，以成本效益和快速的方式对许多疾病进行此类疾病的检测。我们的实验室最近证明，可以通过质谱法进行生物样品，没有或最少的样品制备，通过使用液体MALDI质谱法进行有效分析。与雷丁大学的农业系和乳制品研究中心和乳制品研究中心（CEDAR）合作（CEDAR）（CEDAR）（CEDAR）（CEDAR）（CEDAR）（CEDAR）（CEDAR）（CEDAR）及其在600个牛群中进行了大约600个牛群的研究，我们的范围为较快的动物而言，我们的范围是较快的，我们的范围是基于较快的动物。质谱法。该工作流程应允许对农业重要的疾病和条件进行早期和具体的检测，从而利用最大的质谱法在高度敏感，快速且廉价地表征我们的农场动物及其农产品的健康方面的巨大潜力。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Rapid Liquid AP-MALDI MS Profiling of Lipids and Proteins from Goat and Sheep Milk for Speciation and Colostrum Analysis.

DOI：
10.3390/proteomes8030020
发表时间：
2020-08-21
期刊：
Proteomes
影响因子：
3.3
作者：
Piras C;Ceniti C;Hartmane E;Costanzo N;Morittu VM;Roncada P;Britti D;Cramer R
通讯作者：
Cramer R

LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics.

DOI：
10.1039/d1sc05171g
发表时间：
2022-02-09
期刊：
Chemical science
影响因子：
8.4
作者：
Piras C;Hale OJ;Reynolds CK;Jones AKB;Taylor N;Morris M;Cramer R
通讯作者：
Cramer R

LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis.

DOI：
10.1021/acs.jafc.3c01879
发表时间：
2023-09-20
期刊：
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
影响因子：
6.1
作者：
Lellman, Sophie E.;Reynolds, Christopher K.;Jones, A. K. Barney;Taylor, Nick;Cramer, Rainer
通讯作者：
Cramer, Rainer

Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning.