Biology subjects

Carolino, K.

Publications and source records attributed to Carolino, K..

6 recordsLinked to original sources

bioRxiv2024

A novel chemogenomic screening platform for scalable antimalarial drug target identification

Large-scale chemical-genetic screening, or chemogenomics, can faciliate rapid and scalable drug target identification. To establish a chemogenomic screen for antimalarial drug target identification, we leveraged [~]600 Plasmodium berghei artificial chromosomes (PbACs) encoding potential drug targets to generate a systematic overexpression library. PbACs were engineered with DNA barcodes, enabling their quantification within mixed pools using next generation sequencing (barcode sequencing or BarSeq). Pooled transfection of PbACs into the highly genetically tractable Plasmodium knowlesi demonstrated efficient vector uptake and transcription of encoded P. berghei genes. Parasite pools were exposed to antimalarial candidates, with pilot screens probing for known gene-compound associations identifying their targets with high sensitivity. Screening antimalarial inhibitors with unknown mechanisms of action successfully identified pi4k as the target for one novel compound, which was subsequently validated using in vitro evolution in Plasmodium falciparum parasites. This sensitive and scalable chemogenomics platform therefore represents a valuable early-stage tool for antimalarial target identification.

microbiology↗

bioRxiv2023

Upper bound on the mutational burden imposed by a CRISPR-Cas9 gene-drive element

CRISPR-Cas9 gene drives (CCGDs) are powerful tools for genetic control of wild populations, with applications from disease eradication to species conservation. However, Cas9 alone and in a complex with gRNA can cause double-stranded DNA breaks at off-target sites, which could increase the mutational load and lead to unintended loss-of-heterozygosity (LOH) events. These undesired effects raise potential concerns about the long-term evolutionary safety of CCGDs, but the magnitude of these effects is unknown. To measure how the presence of a CCGD or a Cas9 alone in the genome affects the rates of LOH events and de novo mutations, we carried out a mutation accumulation experiment in yeast Saccharomyces cerevisiae. We found no detectable effects on the genome-wide rates of mutations or LOH events. Our power calculations suggest that CCGD or Cas9 affect these rates by less than 30%, which is much less than natural variation for these traits in yeast. A more detailed examination shows that CCGD or Cas9 may alter the lengths and genomic distributions of LOH events, but the statistical support for these effects is weak. Thus, our results demonstrate that CCGDs impose at most a weak additional mutational burden in the yeast model. Although mutagenic effects of gene drives need to be further evaluated in other systems, our results add credence to the proposition that the evolutionary risks posed by well designed gene drives are likely acceptable.

evolutionary biology↗

bioRxiv2022

Plasmodium exoerythrocytic parasites redirect trafficking of human proteins to the parasitophorous vacuole

Changes in host cell morphology and transcription after apicomplexan parasite infection have long been noted, but there have been few studies of the functional consequences of host cell remodeling. Here we show, using time-dependent immunofluorescence microscopy of multiple human cell lines (HepG2, HC-04, Huh7.5.1 and primary human hepatocytes), infected with multiple Plasmodium species (Plasmodium berghei, P. falciparum and P. vivax (hypnozoites and schizonts)), and antibodies to multiple human proteins (HsNR4A3, HsMUC13, HsGOLGA8A, HsCGA, HsBiP, HsCXCL2), that human protein trafficking is extensively modified in Plasmodium infected cells. Using conventional as well as ultrastructure expansion microscopy we show that newly-synthesized human proteins are trafficked to the parasitophorous vacuole instead of the infected-cell plasma membrane, nucleus or extracellular space. Universal redirection of human signaling proteins cells the parasitophorous vacuole may provide a mechanistic explanation for how apicomplexan parasites can block host cells response to infection.

cell biology↗

bioRxiv2021

OXPHOS deficiencies affect peroxisome proliferation by downregulating genes controlled by the SNF1 signaling pathway

How environmental cues influence peroxisome proliferation, particularly through other organelles, remains largely unknown. Yeast peroxisomes metabolize all fatty acids (FA), and methylotrophic yeasts also metabolize methanol. NADH and acetyl-CoA, the products of these pathways enter mitochondria for ATP production, and for anabolic reactions. During the metabolism of FA and/or methanol, the mitochondrial oxidative phosphorylation (OXPHOS) pathway accepts NADH for ATP production and maintains cellular redox balance. Remarkably, peroxisome proliferation in Pichia pastoris was abolished in NADH shuttling and OXPHOS mutants affecting complex I or III, or by the mitochondrial uncoupler, 2,4-dinitrophenol (DNP), indicating ATP depletion causes the phenotype. We show that mitochondrial OXPHOS deficiency inhibits the expression of several peroxisomal proteins implicated in FA and methanol metabolism, as well as in peroxisome division and proliferation. These genes are regulated by the Snf1 complex (SNF1), a pathway generally activated by high AMP and low ATP. Consistent with this mechanism, in OXPHOS mutants, Snf1 is activated by phosphorylation, but Gal83, its interacting subunit, fails to translocate to the nucleus. Phenotypic defects in peroxisome proliferation observed in the OXPHOS mutants, and phenocopied by the{Delta} gal83 mutant, were rescued by deletion of three transcriptional repressor genes (MIG1, MIG2 and NRG1) controlled by SNF1 signaling. We uncovered here the mechanism by which peroxisomal and mitochondrial metabolites influence redox and energy metabolism, while also influencing peroxisome biogenesis and proliferation, thereby exemplifying interorganellar communication and interplay involving peroxisomes, mitochondria, cytosol and the nucleus. We discuss the physiological relevance of this work in view of human OXPHOS deficiencies.

cell biology↗

bioRxiv2021

Defining the Yeast Resistome through in vitro Evolution and Whole Genome Sequencing

In vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in the model microbe, Saccharomyces cerevisiae. Analysis of 355 curated, laboratory-evolved clones, resistant to 80 different compounds, demonstrates differences in the types of mutations that are identified in selected versus neutral evolution and reveals numerous new, compound-target interactions. Through enrichment analysis we further identify a set of 137 genes strongly associated with or conferring drug resistance as indicated by CRISPR-Cas9 engineering. The set of 25 most frequently mutated genes was enriched for transcription factors and for almost 25 percent of the compounds, resistance was mediated by one of 100 independently derived, gain-of-function, single nucleotide variants found in 170-amino-acid domains in two Zn2C6 transcription factors, YRR1 and YRM1 (p < 1x 10 -100). This remarkable enrichment for transcription factors as drug resistance genes may explain why it is challenging to develop effective antifungal killing agents and highlights their important role in evolution.

genetics↗

bioRxiv2020

Discovering biomarkers of chemotherapy resistance using in vitro evolution in haploid human cells

BackgroundIn vitro evolution and whole genome analysis has proven to be a powerful method for studying the mechanism of action of small molecules in many haploid microbes but has generally not been applied to human cell lines in part because their diploid state complicates the identification of variants that confer drug resistance. To determine if haploid human cell could be used in MOA studies, we evolved resistance to five different anticancer drugs (doxorubicin, gemcitabine, etoposide, topotecan, and paclitaxel) using a near-haploid cell line (HAP1) and then analyzed the genomes of the drug resistant clones, developing a bioinformatic pipeline that involved filtering for high frequency alleles predicted to change protein sequence, or alleles which appeared in the same gene for multiple independent selections with the same compound. Applying the filter to sequences from 28 drug resistant clones identified a set of 21 genes which was strongly enriched for known resistance genes or known drug targets (TOP1, TOP2A, DCK, WDR33, SLCO3A1). In addition, some lines carried structural variants that encompassed additional known resistance genes (ABCB1, WWOX and RRM1). Gene expression knockdown and knockout experiments of 10 validation targets showed a high degree of specificity and accuracy in our calls and demonstrates that the same drug resistance mechanisms found in diverse clinical samples can be evolved, discovered and studied in an isogenic background.

cancer biology↗