SUMMARY The human microbiota greatly affects physiology and disease. However, the contribution of bacteria to the response to chemotherapeutic drugs remains poorly understood. Caenorhabditis elegans and its bacterial diet provide a powerful system to study host-bacteria interactions. Here, we use this system to study how bacteria affect the C. elegans response to chemotherapeutics. We find that different bacterial species can increase the response to one drug yet decrease the effect of another. We perform genetic screens in two bacterial species using three chemotherapeutic drugs, 5-fluorouracil (5-FU), 5-fluoro-2′-deoxyuridine (FUDR) and camptothecin (CPT). We find numerous bacterial nucleotide metabolism genes that affect drug efficacy in C. elegans. Surprisingly, we find that 5-FU and FUDR act through bacterial ribonucleotide metabolism to elicit their cytotoxic effects in C. elegans, rather than by thymineless death or DNA damage. Our study provides a blueprint for characterizing the role of bacteria in the host response to chemotherapeutics.

SUMMARY Gene regulatory networks (GRNs) comprising interactions between transcription factors (TFs) and regulatory loci control development and physiology. Numerous disease-associated mutations have been identified, the vast majority residing in non-coding regions of the genome. As current GRN mapping methods test one TF at a time and require the use of cells harboring the mutation(s) of interest, they are not suitable to identify TFs that bind to wild type and mutant loci. Here, we use gene-centered yeast one-hybrid (eY1H) assays to interrogate binding of 1,086 human TFs to 246 enhancers, as well as to 109 non-coding disease mutations. We detect both loss and gain of TF interactions with mutant loci that are concordant with target gene expression changes. This work establishes eY1H assays as a powerful addition to the toolkit of mapping human GRNs and for the high-throughput characterization of genomic variants that are rapidly being identified by genome-wide association studies.

DNA repair is expected to be a modulator of underlying mutation rates, however the major factors affecting the distribution of DNA repair pathways have not been determined. The Proteomic Constraint theory proposes that mutation rates are inversely proportional to the amount of heredity information contained in a genome, which is effectively the proteome. Thus, organisms with larger proteomes are expected to possess more efficient DNA repair. We show that an important factor influencing the presence or absence of four DNA repair genes mutM, mutY, mutL, and mutS is indeed the size of the bacterial proteome. This is true both of intracellular and other bacteria. In addition, the relationship of DNA repair to genome GC content was examined. In principle, if a DNA repair pathway is biased in the types of mutations it corrects, this may alter the genome GC content. The presence of the mismatch repair genes mutL and mutS was not correlated with genome GC content, consistent with their involvement in an unbiased DNA repair pathway. In contrast, the presence of the base excision repair genes mutM and mutY, whose products both correct GC → AT mutations, was positively correlated with genome GC content, consistent with their biased repair mechanism. Phylogenetic analysis however indicates that the relationship between the presence of mutM and mutY genes and genome GC content is not a simple one.

In our group, we aim to understand metabolism in the nematode Caenorhabditis elegans and its relationships with gene expression, physiology and the response to therapeutic drugs. Visualization of the metabolic pathways that comprise the metabolic network is extremely useful for interpreting a wide variety of experiments. Detailed annotated metabolic pathway maps for C. elegans is mostly limited to pan-organismal maps, many with incomplete or inaccurate pathway and enzyme annotations. Here we present WormPaths, which is composed of two parts: 1) the careful manual annotation of metabolic genes into pathways, categories and levels, and 2) 62 pathway maps that include metabolites, metabolite structures, genes, reactions, and pathway connections between maps. These maps are available on the WormFlux website. We show that WormPaths provides easy-to-navigate maps and that the different levels in WormPaths can be used for metabolic pathway enrichment analysis of transcriptomic data. In the future we envision further developing these maps to be more interactive, with an analogy of road maps that are available on mobile devices.

Metabolism of host-targeted drugs by the microbiome can substantially impact host treatment success. However, since many host-targeted drugs inadvertently hamper microbiome growth, repeated drug administration can lead to microbiome evolutionary adaptation. We tested if evolved bacterial resistance against host-targeted drugs alters their drug metabolism and impacts host treatment success. We used a model system of C. elegans, its bacterial diet, and two fluoropyrimidine chemotherapies. Genetic screens revealed that most of loss-of-function resistance mutations in Escherichia coli also reduced drug toxicity in the host. We found that resistance rapidly emerged in E. coli under natural selection and converged to a handful of resistance mechanisms. Surprisingly, we discovered that nutrient availability during bacterial evolution dictated the dietary effect on the host – only bacteria evolving in nutrient-poor media reduced host drug toxicity. Our work suggests that bacteria can rapidly adapt to host-targeted drugs and by doing so may also impact the host.