Seeking EV Fertility Biomarkers in Dairy Cows Using SWATH-MS

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Queensland researchers have embarked on EV/mass spec projects that may improve predictions of dairy cow fertility, and outcomes for pregnant women.

As dairy cow fertility underpins the viability and productivity of every dairy farm, the reproductive management of dairy herds is a critical aspect of dairy farming. Despite major advances in the understanding of health, nutrition, and genetics, however, there is room to improve predictions of fertility. Currently, the selection of dairy cattle for breeding is based on Breeding Worth, a ranking system that combines Breeding Values (an estimate of an animal’s genetic merit for a particular trait) along with economic considerations. Although the use of Breeding Values has greatly enhanced reproductive management and the overall performance of the dairy sector, there is room for improvement.

“Fertility Breeding Value is not terribly specific,” explains Queensland University of Technology PhD student, Natalie Turner. “There are a lot of supposedly high-fertile animals that end up being poorly fertile, and then there are a lot of animals predicted to have low fertility which end up being good reproducers – so there’s definitely room for improvement.”  

As outlined in her review titled “Exosomal Cargo May Hold the Key to Improving Reproductive Outcomes in Dairy Cows”, Turner and colleagues are looking to plasma extracellular vesicles (EVs) for their ability to help refine predictions of fertility in cattle.<super-script>1<super-script>

To set the groundwork for her PhD studies, Turner has been focused on improving sample preparation methods for future mass spectrometry analysis. “I’ve also done some verification and validation of our current isolation strategies for small EVs, and I now have my results which I’m going through now.”

Harnessing SWATH-MS for biomarker discovery

To determine candidate biomarkers that can be taken forward for future experiments, Turner and her team are using a quantitative mass spectrometry tool known as SWATH-MS (sequential window acquisition of all theoretical mass spectra)-MS, a variant of data-independent acquisition (DIA) methods.<super-script>2<super-script>  

“Data dependent acquisition (DDA) is the more traditional shotgun mass spectrometry approach that people used in the past. It's sensitive, but it's not very reproducible, and therefore, is considered to be quite a biased approach and not generally used for quantitation,” says Turner. “In contrast, SWATH is a type of DIA and it doesn’t rely on the fragmentation of the most abundant precursor ions, but rather fragments all precursor ions within a selected mass range. So, you can glean a lot more information from the same sample, over what is essentially the same timed run as you used for data dependent acquisition.”

The main benefit of SWATH-MS is that it can be used to not only identify proteins, but quantify them as well, explains Turner. “It just requires additional skills with regards to data analysis, and there are different software tools available. You can compare the levels between your groups of interest and come up with a fold-change in peptides or proteins. And that's how you develop your candidate list – of biomarkers in our case.”  

From left to right: Toni Mitchell (RA), Kanchan Vaswani (RA), Keith KwanCheung (PhD student), Dr. Jayden Logan (post-doc) (back), Marko Dimik (PhDstudent, front), Prof Murray D. Mitchell (group leader), Isabella Morean Garcia(work-integrated learning (WILS) student, back), Somerville high schoolstudents on placement x 3 (in uniform), Pevindu Abeysinghe (PhD student,front), Natalie Turner (PhD student, back).

Approaches to cross-run comparisons  

SWATH-MS is quantitative, enabling comparisons of different samples and groups within a run. But what if you wanted to compare across runs? Turner explains: “Within the SWATH protocols, you have what's called your indexed retention time calibrators. These are peptides that are spiked into your sample, and therefore, they allow cross-run comparisons. So that's really important, because a lot of the quantitation is reliant on where the peptides actually elute (at what time point) – not just the intensity peaks that you see. So, if you were comparing different runs at different times, as long as those calibrators were present in both of your preparations, you could do that.”  

“But in saying that, new software has made it possible to pick out common peptides within samples and use those as your calibrators now as well. It's not 100% necessary to have those calibrators there – they’re useful and easy, the software tool has them already as a setting in the software, and you can choose them easily. But if not, you can develop your own calibrators instead for cross-run comparisons.”

Such capabilities might be more relevant in the future, when additional samples are collected to assess samples from cows that fall in the mid-range of the fertility spectrum. “The idea is to use low- and high-fertility to get that list of candidates together, and then go back to those mid-range cattle to see how well reproductive performance can be predicted. That would be very interesting and useful, because in terms of developing some kind of reference range for fertility, that's the direction that we need to go,” says Turner.

 

Eyes on EV biomarkers, but plasma not forgotten  

Although the project is EV-focused, plasma samples are also being analysed. “It might be the case that we pick up good biomarkers in both plasma and in exosomes, or in just one sample type – but it's definitely worth looking at both. From literature and my own data, I can see that they give very different pieces of information already by mass spectrometry. But I think from a biological molecular perspective, exosomes or EVs are interesting because they are so heavily involved in cell-to-cell signalling. So therefore, you might see better a representation of molecular pathways that are up- or downregulated from your EV proteins, rather than just those circulating in plasma.”

“The main focus is the discovery aspect – now that we have this great technology available to us, we can do this huge, proteome-wide screen of all exosomal proteins that are in our samples, and then come up with a really good candidate list from that. We use qEVoriginal columns/70 nm. We were actually so excited about getting the Automatic Fraction Collector not too long ago and it’s been amazing. So possibly we will have even better data coming from our lab.”

PhD project part of wider progress in the EV-agriculture and EV-reproductive space

Turner’s project is among a range of exciting, collaborative EV-based projects underway, including work on tick resistance in cattle alongside colleague Pevindu Abeysinghe (in collaboration with a cattle farm in Nindooinbah, Queensland)<super-script>3,4<super-script> and infant formula experiments (funded by Mead Johnson). The fertility biomarker work is supported by a DairyNZ discovery grant, and milk samples have been provided by The University of Queensland Gatton Campus for analysis.  

She is under the supervision of Murray Mitchell, Professor at QUT, Child & Reproductive Health Research Group, School of Biomedical Sciences, Faculty of Health, and co-supervisor Pawel Sadowski, head of Proteomics and Small Molecule Mass Spectrometry Core at the Queensland University of Technology.  

Mitchell has a valuable collaboration with the Queensland Family Cohort Study, a prospective, observational, longitudinal study which will recruit 12,500 pregnant families from across the state of Queensland.<super-script>5<super-script> From this, valuable samples will be obtained and analysed, explains Mitchell:  

“We will be looking at longitudinal changes in multiple populations of the exosomes and trying to see if we can get a prognostic (not just a diagnostic) for the risk of things like high-risk pregnancies, preterm labour, and diabetes – and sadly, stillbirth, which we’ll do with the Stillbirth Research Center, which is 100 yards up the road at the Mater Research Institute.

The Queensland family cohort is just an incredible blessing for us to have access to these wonderful samples. Downstream experiments will involve studying EVs in in vitro culture systems, just to see what effects they may produce in vitro using bovine endometrial cell lines that we’ve used previously.

We have a range of these terrific clinical collaborators. The Queensland family cohort is run by Professor Vicki Clifton, out of the Mater Research Institute. We’ll also be working with Sailesh Kumar, who is the head of obstetrics there, and we’ll be working with all of the people at RBWH (Royal Brisbane and Women’s Hospital). We have a PhD student starting, Keith Kwan Cheung – so watch this space and come back next year, and we'll probably have Keith here doing what Natalie's been doing, telling you about that research.”  

With the SWATH-MS groundwork well underway, and a network of valuable collaborations, the group is well placed to explore how EVs might be able to improve outcomes – both for pregnant women, and on the dairy farm.

Image credit: smspsy, stock.adobe.com (Header Image)

References

  1. Turner N, Abeysinghe P, Sadowski P, Mitchell MD.Exosomal Cargo May Hold the Key to Improving Reproductive Outcomes in DairyCows. International Journal of MolecularSciences. 2021;22(4):2024. doi:10.3390/ijms22042024
  2. Ludwig C, Gillet L, Rosenberger G, Amon S, Collins BC,Aebersold R. Data‐independent acquisition‐based SWATH ‐ MS for quantitativeproteomics: a tutorial. Molecular Systems Biology.2018;14(8). doi:10.15252/msb.20178126
  3. Turner N, Abeysinghe P, Peiris H, et al. Proteomicprofiling of plasma-derived small extracellular vesicles: a novel tool forunderstanding the systemic effects of tick burden in cattle. Journal of Animal Science.2022;100(2):skac015. doi:10.1093/jas/skac015
  4. Abeysinghe P, Turner N, Peiris H, et al. DifferentiallyExpressed Extracellular Vesicle, Exosome and Non-Exosome miRNA Profile in Highand Low Tick-Resistant Beef Cattle. Frontiers in Cellular andInfection Microbiology. 2021;11:780424. doi:10.3389/fcimb.2021.780424
  5. Borg D, Rae K, Fiveash C, et al. Queensland FamilyCohort: a study protocol. BMJ Open. 2021;11(6):e044463.doi:10.1136/bmjopen-2020-044463

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