Biology subjects

de los Santos, E. L.

Publications and source records attributed to de los Santos, E. L..

3 recordsLinked to original sources

bioRxiv2026

Structure-Led Exploration of the Metagenome Yields Novel RNA-Guided Nucleases with Broad PAM Diversity

Compact RNA-guided nucleases with favorable targeting properties are challenging to discover due to their low natural abundance. Here, we develop a structure-led search strategy -leveraging predicted protein folds and sequence-independent similarity metrics -to systematically identify extremely low-homology compact RNA-guided nucleases across vast metagenomic datasets with high computational efficiency. Homology clustering resolved these proteins into distinct groups, for which we performed comprehensive PAM profiling and evaluated editing efficiency in eukaryotic cells. This structure-guided discovery revealed a previously undiscovered landscape of compact nuclease subtypes that exhibit extensive protospacer-adjacent motif (PAM) diversity, expanding the targeting potential of compact editors. Comparative analysis across the novel RNA-guided nuclease families demonstrates that compact systems are not intrinsically limited to highly constrained PAMs but instead have a broad and previously unknown breadth of genome targeting capabilities, comparable to that of Cas9 and far exceeding common transposon- derived systems. Additionally, this search revealed that a compact transposon-associated motif (TAM) is a prerequisite for the emergence of a CRISPR-Cas system from ancestral transposons, before protein domain expansions increase the target length and specificity constraints. These results enrich the catalog of RNA-guided nuclease architectures and contribute validated compact genome editing tools with broad and diverse PAM recognition, which may have therapeutic applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/714800v2_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@19ccdc9org.highwire.dtl.DTLVardef@18a5027org.highwire.dtl.DTLVardef@1945836org.highwire.dtl.DTLVardef@2b5bae_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2019

Pentamycin biosynthesis in Philippine Streptomyces sp. S816: Cytochrome P450-catalysed installation of the C-14 hydroxyl group

Pentamycin is a polyene antibiotic, registered in Switzerland for the treatment of vaginal candidiasis, trichomo-niasis and mixed infections. Chemical instability has hindered its wide-spread application and development as a drug. Here we report the identification of Streptomyces sp. S816, isolated from Philippine mangrove soil, as a pentamycin producer. Genome sequence analysis identified the putative pentamycin biosynthetic gene cluster, which shows a high degree of similarity to the gene cluster responsible for filipin III biosynthesis. The ptnJ gene, which is absent from the filipin III biosynthetic gene cluster, was shown to encode a cytochrome P450 capable of converting filipin III to pentamycin. This confirms that the cluster directs pentamycin biosynthesis, paving the way for biosynthetic engineering approaches to the production of pentamycin analogues. Several other Streptomyces genomes were found to contain ptnJ orthologues clustered with genes encoding polyketide synthases that appear to have similar architectures to those responsible for the assembly of filipin III and pentamycin, suggesting pentamycin production may be common in Streptomyces species.

biochemistry↗

bioRxiv2017

clusterTools: Proximity Searches For Functional Elements To Identify Putative Biosynthetic Gene Clusters

Motivation: The low cost of DNA sequencing has accelerated research in natural product biosynthesis allowing us to rapidly link small molecules to the clusters that produce them. However, the large amount of data means that the number of putative biosynthetic gene clusters (BGCs) far exceeds our ability to experimentally characterize them. This necessitates the need for development of further tools to analyze putative BGCs to flag those of interest for further characterization.\n\nResults: Clustertools implements a framework to aid in the characterization of putative BGCs. It does this by or-ganizing genomic information on coding sequences in a way that enables directed, hypothesis-driven queries for functional elements in close physical proximity of each other. Genomic sequence databases can be constructed in clusterTools with an interface to the NCBI Genbank and Genomes databases, or from private sequence databases. clusterTools can be used either to identify interesting BGCs from a database of putative BGCs, or on databases of genomic sequences to identify and download regions of interest in the DNA for further processing and annotation in programs such as antiSMASH. We have used clusterTools to identify putative and known biosynthetic gene clus-ters involved in bacterial polyketide alkaoloid and tetronate biosynthesis.\n\nAvailability and Implementation: Clustertools is implemented in Python and is available via the AGPL. Stand-alone versions of clusterTools are available for Macintosh, Windows, and Linux upon registration (https://goo.gl/forms/QRKTkpqiA0g31IWp1). The source-code is available at https://www.github.com/emzodls/clusterArch.\n\nSupplementary information: A manual describing the Python toolkit that powers clusterTools, as well as the HMMs constructed for the tetronate search is available online.

bioinformatics↗