Virginia Pérez

Happy birthday Jenny! 🎂 Greetings from Spain!

20.11.2025 19:50 — 👍 0    🔁 0    💬 1    📌 0

A group of smiling, slightly damp scientists under umbrellas on the streets on London

Some of the lab on our outing to lunch at Shanghai Family - definitely an umbrella sort of day here in London! We were saying welcome to our newest members, Milica and Simon, and farewell to visiting EMBO fellow Virginia. Any excuse for dumplings. 🥟

29.10.2025 17:03 — 👍 3    🔁 1    💬 0    📌 0

🧫 With this work we have been able to characterise taxonomically and functionally the urobiome of patients with SLE, as well as identify new biomarkers for the diagnosis of renal SLE.

26.09.2025 20:06 — 👍 1    🔁 0    💬 0    📌 0

Identification of urinary bacterial genes as biomarkers for non-invasive diagnosis of renal lupus - Biomarker Research Background Systemic lupus erythematosus (SLE) is a complex autoimmune disease that often affects the kidneys, causing lupus nephritis. Diagnosis of this affection currently relies on kidney biopsy, an invasive and complex procedure. This study explores the diagnostic value of biomarkers based in the urobiome – the microbial community of the urinary tract – in patients with renal SLE. Methods This study enrolled 585 female subjects including Healthy controls, non-renal and renal SLE patients. The taxonomic and functional differences of the urobiome in patients with SLE, as well as in the metabolites of interest, were identified by 16S rRNA profiling with PICRUSt functional inference and nuclear magnetic resonance (NMR). The accuracy of the identified biomarkers was tested by building random forest (RF) classification models. Furthermore, the results were validated in an independent cohort composed by 30 controls, 30 non-renal and 30 renal SLE patients. Results Bacterial gene-based biomarkers with an AUC value of 0.7 ± 0.07 and 0.67 ± 0.07 to distinguish renal from non-renal SLE cases were identified. These biomarkers were validated in a validation cohort using quantitative PCR (qPCR), demonstrating their robust diagnostic performance. Furthermore, our analysis uncovered significant urobiome dysbiosis and distinct bacterial functional profile in both groups of SLE patients, with notable differences in amino acid metabolism pathways, particularly those involving valine and leucine, which were assessed by NMR-based urinary metabolite quantification. Conclusions Some bacterial genes have been identified in the urobiome of SLE patients that allow differentiation between those with renal and non-renal lupus. These findings offer valuable insight into the association between the urobiome and SLE presentation, and lay the foundation for developing novel diagnostic tools that overcome the limitations of current methods, thereby improving patient care.

🚨🆕 Very happy to share our latest published work, which includes some results of my doctoral thesis: “Identification of urinary bacterial genes as biomarkers for non-invasive diagnosis of renal lupus” biomarkerres.biomedcentral.com/articles/10....

26.09.2025 20:06 — 👍 1    🔁 1    💬 1    📌 0

First times 🔬

30.08.2025 21:32 — 👍 1    🔁 0    💬 0    📌 0

Just one month from starting this new adventure as part of my training as a PhD student. During the next few months, I will be doing a short stay in the lab of Prof. @jennyrohn.bsky.social in London as a beneficiary of an EMBO Exchange Scientific Grant. I can't wait to start this new stage! 🧫

26.06.2025 19:23 — 👍 1    🔁 0    💬 0    📌 2

In-depth analysis of the mode of action of resveratrol: genome-wide characterization of G-quadruplex binding properties - Cellular & Molecular Biology Letters Background Resveratrol (RSV) is one of the most studied and used biomolecules, for which many pharmacological effects targeting multiple tissues have been described. However, a common underlying mecha...

A recent work in our lab has just been published. Don't miss the opportunity to read about resveratrol and a new mechanism of action based on G-quadruplexes.

cmbl.biomedcentral.com/articles/10....

26.06.2025 17:43 — 👍 2    🔁 0    💬 0    📌 0