Biology subjects

Urbaitis, T.

Publications and source records attributed to Urbaitis, T..

3 recordsLinked to original sources

bioRxiv2026

A cold-adapted Cas9 nuclease from the deep ocean

The abundance of CRISPR systems in bacteria and archaea fuels the search for Cas nucleases that perform where established enzymes fail. Deep Ocean 1 Cas9 (DO1Cas9) is to our knowledge the first Cas9 nuclease characterized from the deep ocean, recovered from a metagenomic sample at 1,500 m depth in the Atlantic Ocean. DO1Cas9 shows cold-adapted structural flexibility, thermal susceptibility, salt-dependent stability, higher specificity than SpCas9 and cleaves double-stranded DNA efficiently under cold conditions where mesophilic SpCas9 retains only residual activity. DO1Cas9 edits genomes in diverse organisms such as Caenorhabditis elegans, zebrafish, the marine tunicate Oikopleura dioica, and the malaria parasite Plasmodium falciparum. In the marine bacterium Marinomonas mediterranea, DO1Cas9 programmed against an invading phage reduced plaquing efficiency about 10-fold more than SpCas9. These results expand the CRISPR-Cas9 toolbox with a nuclease for cold-chain editing and marine biotechnology.

genetics↗

bioRxiv2023

TemStaPro: protein thermostability prediction using sequence representations from protein language models

MotivationReliable prediction of protein thermostability from its sequence is valuable for both academic and industrial research. This prediction problem can be tackled using machine learning and by taking advantage of the recent blossoming of deep learning methods for sequence analysis. These methods can facilitate training on more data and, possibly, enable development of more versatile thermostability predictors for multiple ranges of temperatures. ResultsWe applied the principle of transfer learning to predict protein thermostability using embeddings generated by protein language models (pLMs) from an input protein sequence. We used large pLMs that were pre-trained on hundreds of millions of known sequences. The embeddings from such models allowed us to efficiently train and validate a high-performing prediction method using over one million sequences that we collected from organisms with annotated growth temperatures. Our method, TemStaPro (Temperatures of Stability for Proteins), was used to predict thermostability of CRISPR-Cas Class II effector proteins (C2EPs). Predictions indicated sharp differences among groups of C2EPs in terms of thermostability and were largely in tune with previously published and our newly obtained experimental data. Availability and ImplementationTemStaPro software and the related data are freely available from https://github.com/ievapudz/TemStaPro and https://doi.org/10.5281/zenodo.7743637.

bioinformatics↗

bioRxiv2020

Biochemically diverse CRISPR-Cas9 orthologs

CRISPR-Cas9 nucleases are abundant in microbes. To explore this largely uncharacterized diversity, we applied cell-free biochemical screens to rapidly assess the protospacer adjacent motif (PAM) and guide RNA (gRNA) requirements of novel Cas9 proteins. This approach permitted the characterization of 79 Cas9 orthologs with at least 7 distinct classes of gRNAs and 50 different PAM sequence requirements. PAM recognition spanned the entire spectrum of T-, A-, C-, and G-rich nucleotides ranging from simple di-nucleotide recognition to complex sequence strings longer than 4. Computational analyses indicated that most of this diversity came from 4 groups of interrelated sequences providing new insight into Cas9 evolution and efforts to engineer PAM recognition. A subset of Cas9 orthologs were purified and their activities examined further exposing additional biochemical diversity. This constituted both narrow and broad ranges of temperature dependence, staggered-end DNA target cleavage, and a requirement for longer stretches of homology between gRNA and DNA target to function robustly. In all, the diverse collection of Cas9 orthologs presented here sheds light on Cas9 evolution and provides a rich source of PAM recognition and other potentially desirable properties that may be mined to expand the genome editing toolbox with new RNA-programmable nucleases.

biochemistry↗