BDB-Lab Winter 2022 Update
BDB-Lab Winter 2022 Update
Dogs. SemiBin2. ResFinderFG2. and more
Coming up
5 February: deadline for Spring/Summer remote internship applications.
Winter Focus: Pet’s microbiome research by Anna Cuscó
Why is it important to study the microbiome of pets?
Most pet owners consider their animals as family members and care about their well-being and health. The microbiome has a great impact on human and animal health and has key roles in many physiological processes in the body (e.g., immunity, digestion, and development). So, studying our pets’ microbiomes can help us understand their composition, functionality, and action mechanisms, and how these change in disease.
Apart from the benefit to our pets’ health, especially in cities and highly urbanized areas, pets spend most of their life within the indoor domestic environment in close physical contact with their owners. Thus, households with pets are a great example of a One Health scenario: many of the same microbes colonize animals and humans within the shared ecosystem promoting health or potentially causing disease.
These would be the two main reasons why it is important to study the microbiome of pets. It is also worth mentioning that dog gut and skin microbiome have been considered a good simplified model of the human microbiome.
How does your approach differ from previous studies?
Most studies on pets, mostly dog and cat, and gut microbiomes rely on 16S rRNA gene amplification and sequencing due to their low cost and straightforward analysis. 16S rRNA-based microbiome studies provide taxonomic and compositional information at the family or genus level but cannot retrieve species- and strain-level composition and functional information.
In contrast, metagenomics captures and sequences a less biased sample of the DNA within a complex sample, detecting the complete microbiome functional potential by looking at the genes. However, most metagenomics studies are short-read based (shotgun metagenomics), resulting in fragmented metagenome-assembled genomes (MAGs) rather than high-quality ones.
In this project, we will use long-read metagenomics to understand the complexity of the pet gut microbiome and retrieve high-quality MAGs. High-quality MAGs are similar to complete genomes since they are highly complete with low contamination, and they harbor ribosomal genes and at least 18 out of 20 canonical tRNAs (according to MIMAG criteria). Another significant advantage over short-read metagenomics is the correct assembly of mobile genetic elements, which include plasmids, bacteriophages, insertion sequences, and transposable elements.
Where do you plan to take the project in the future?
In the near future, during my postdoc at the BDB, I plan to obtain insights into the pet dog gut microbiomes, their key microbial members, and their potential functions using high-quality MAGs. The potential results could be useful for informed strategies in small animal veterinary medicine and nutrition fields: from better strategies towards pathogen surveillance to tailored investigation and development of prebiotics, probiotics, and other microbiome modulation approaches.
Overall, I would love to continue advancing in this field, incorporating the latest new technologies to get interesting data, and to make actionable steps to apply the findings to real situations.
Can you also tell us a bit about yourself: what was your path to get here?
I am a biotechnologist (Autonomous University of Barcelona, Barcelona, Spain) with a master's degree in biomedical research (Pompeu Fabra University, Barcelona, Spain). I did an industrial Ph.D. study between the Autonomous University of Barcelona and Vetgenomics (Barcelona, Spain) supervised by Dr. Olga Francino. During my Ph.D. is where I first began working with microbiomes. Specifically, my Ph.D. thesis focused on characterizing healthy dogs' skin microbiomes through 16S rRNA gene sequencing using next-generation and single-molecule sequencing. Later on, I continued working in Vetgenomics, being responsible for microbiome and long-read DNA sequencing projects and setting up Nanopore sequencing approaches for microbial genomics and microbiome profiling.
Despite beginning my scientific journey at a molecular biology lab, I slowly switched to the dry lab and spent more and more time analyzing data rather than producing it at the lab bench. I aimed to expand and strengthen my bioinformatics skills by doing a postdoc, and I wanted to do it abroad since my research experience had always been in Spain. So, I returned to academia in August 2021 to join the Big Data Biology Lab led by Luis Pedro Coelho (Fudan University, Shanghai, China).
Where can people find you and get in touch?
Feel free to contact me by e-mail. You can also find me on Twitter and recently on Mastodon.
BDB-Lab Updates
Preprints. SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing: describes the novel functionality available on SemiBin2. ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics in which Svetlana and Luis collaborated with our EMBARK colleagues to build the new version of the ResFinderFG database (which collates data on functional metagenomics).
Presentations. Svetlana presented at the Serbian Society for Bioinformatics and Computational Biology. We had two guests in our group meeting: Rémi Gschwind talked about the ResFinderFG2 v2.0 database, and Katarzyna Sidorczuk talked about the effects of negative benchmarking on antimicrobial peptide prediction using different architectures.
People. Luis is back in Shanghai as well as most of our team! We also welcome Chuan Xuan, who recently joined our group as an intern. Shaojun Pan was awarded a National Ph.D. Scholarship from the Chinese government and Anna Cuscó was awarded an RFIS-I grant from the National Natural Science Foundation of China (NSFC). Congratulations to both!
Tools. SemiBin had several releases in the last few months (versions 1.2, 1.3, and 1.4 in close succession). The biggest changes are the introduction of self-supervised learning and improvements to long-read sequencing.
Blogposts. Our summer interns produced blog posts reporting their work. A blog post by Breno Lívio discusses how to compute the rarefaction curves for the GMSC project. Jelena Somborski also released a blog post telling us more about the challenges and importance of choosing the right color palettes for the correct and precise visualization of data.
Other. We posted a few videos on our YouTube channel on how we made SemiBin faster. We will be publishing more YouTube videos going forward, though.
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