Miguel Angel García-Campos

Miguel Angel García-Campos

A biologist working on RNA modifications .

About

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Hello, my name is Miguel. I am a biologist with great interest in understanding life from a quantitative and systematic perspective. My latest work focused on advancing the understanding of RNA modifications, working in the development of technologies to detect and quantify different moieties across whole transcriptomes at the Schwartz Lab of the Weizmann Institute of Science. I am curently looking for a prospective lab to continue my work as a postdoctoral fellow in a more translational research environment. I am interested in taking my experience and expertise to the fields of aging, cancer, and immunosenescence.

My latest work Pan-Mod-seq, published in the Cell journal, is an RNA-seq technology that allows to detect and measure 16 different RNA moieties in the same workflow, across dozens of samples. This allowed us to interrogate 14 species across the three domains of the tree of life, six bacterial, six archeal, and two eukaryotic organisms, adressing the potential dynamic nature of rRNA modifications under different growth conditions. The growing conditions we used involved gradients of temperatures, pH, salinity, and growth density. Our results showed that rRNA modifications have evolutionarily relevant conservation across species of the same domain, and although most detected rRNA modifications were not proven to be dynamic in mesophiles, around 50% of them were dynamic in extremophiles. Furthermore, our results showed that these modifications can work synergistically to stabilize rRNA under high temperatures, having an exquisite regulation mediated by the coupling of secondary structure and temperature change.

I have also developed software to facilitate the processing of RNA-seq data. txtools is an R package that processes RNA-seq reads alignments into transcriptomic-oriented tables. Enabling a quick and simplified analysis, to closely inspect summarized RNA-seq data per transcript, at nucleotide resolution.

Furthermore, I worked in the development ofMAZTER-seq, Cell, an RNA-seq technology that is able to detect and quantify m6A, the most abundant mRNA modification present in all eukaryotes, in a high-throughput, single-nucleotide, and antibody-independent manner. Using this new technology we uncovered a code that dictates m6A deposition across the transcriptomes of mouse and yeast, one of our main conclusions is that m6A deposition is strongly coded in the RNA sequence of each gene.

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Miguel's GitHub contributions in the last year

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