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It is estimated that fungal infections kill greater than 1.6 million people annually, a number that is comparable to the number of deaths associated with tuberculosis. Candida species are the fourth leading cause of hospital-acquired blood infections and Candida albicans is the most common cause of these fungal blood infections (known as candidemia). Immunocompromised individuals, such as those who have HIV/AIDS, those undergoing chemotherapy treatments, or those on broad-spectrum antibiotics, are most likely to develop candidemia. Candidemia is associated with a 20-40% mortality rate. However, when patient treatment for candidemia is delayed for over 48 hours, associated mortality rates increase to 78%. Blood infections can disseminate Candida albicans throughout the body, eventually leading to infection in vital organs like the liver, kidney and brain. Optimal patient outcomes are achieved if antifungal therapy is given within 12 hours after a blood sample is obtained for culture and testing. However, current blood tests cannot reliably detect Candida this early and thus antifungals are not routinely given to patients in this time frame. Counterintuitively, it is believed that some fungi, like many bacteria, are non-harmful residents in small intestines of most adults and this hypothesis is supported by the fact that the most common fungal species in the human gut is Candida albicans. However, intestinal overgrowth of C. albicans is linked to Crohn's disease, and disease-causing forms of C. albicans can arise from commensal strains that once resided in the patient’s gastrointestinal tract. The specific molecular mechanisms by which C. albicans interacts with host immune cells versus intestinal cells, and those that trigger Candida pathogenicity remain unknown. Many strains of Candida albicans have developed resistance to azoles, the major class of drugs used to treat both superficial and systemic infections. In order to develop new treatments, we must better understand host-fungal pathogen biology to determine novel antifungal targets or therapeutics to fight fungal infections at the early stages of infection. In this work, we developed a novel tool that allows us to measure which genes are important to both the host and Candida albicans simultaneously, in specific infection states. We have applied this tool to measure gene expression in Candida albicans interacting with mammalian macrophages and small intestine epithelial cells– at both the population and single cell levels. When examining populations of sorted infection samples, we found that host immune cells both exposed to and infected with fungal cells exhibit similar expression patterns. In contrast, phagocytosed C. albicans exhibit unique expression patterns compared to those merely exposed to macrophages. We found that immune response genes in single, Candida infected macrophages exhibited bimodal expression patterns for some immune response genes. We also observed examples of expression bimodality in live Candida inside of single macrophages. Both Candida albicans and host small intestine epithelial cells demonstrate distinct patterns of expression when exposed to each other at the population level, compared to unexposed controls. However, the magnitude of these differences is dependent on the multiplicity of infection. Some expression programs overlapped with those observed in populations of Candida cells interacting with macrophages, with key differences. We also observed expression bimodality among epithelial cells infected with C. albicans. We believe the information obtained using this technique could be used when considering new antifungal or therapeutics targets; if uniform and high expression of particular in genes in Candida populations phagocytosed by macrophages or invading epithelial cells leads to high and early protein production, these proteins may be effective antifungal targets. Similarly, if some host immune response genes are not expressed in a population of Candida infected macrophages as uniformly and highly as expected, these genes or proteins could be target of a therapeutic for patients with Candida infections that are resistant to azoles.

Au sein des hémopathies malignes B, les plasmocytoses malignes (myélome multiple [MM) et leucémie à plasmocyte [PCLI) occupent une place particulière par leur biologie et leurs aspects cliniques. Biologiquement, elles présentent une forte proportion d’anomalies oncogéniques· (RAS, c-MYC) et de fréquentes altérations de la voie p53 (CDKN2ADel, TP53Del/Mut) qui conduisent, cliniquement, à l’inefficacité des traitements cytostatiques conventionnels. Des lignées cellulaires de MM (HMCls) qui recouvrent en partie la diversité des patients ont été générées depuis 50 ans. Nous avons caractérisé l’exome complet de 33 lignées cellulaires humaines de MM. Les mutations faux-sens sont les plus fréquentes (92%). les HMCLs portent entre 307 et 916 mutant par HMCL, TP53 étant le gène le plus altéré (67%). Des pertes bi-alléliques des voies du cycle cellulaire (CDKN2C, RB1), de la voie NFkB (TRAF3, BIRC2) et de la voie p53 (TP53, CDKN2A) sont fréquentes. La fréquence des mutations/délétion est semblable à celle des patients ( DIS3, PRDM1, KRAS), ou majorée (TP53, CDKN2C, NRAS, PRKD2). la voie MAPK est lá plus altérée (82% des HMCls), principalement par des mutants de RAS: peu décrites, les HMCLs présentent des altérations des voies épigénétiques (73%), de l’ anémie de Fanconi (54%) et très peu d’anonalies directes de la machinerie apoptotique. Nous avons mis en relation les données dexpression, de mutation/délétion et de réponse aux traitements et démontré que l’efficacité de plusieurs traitements est indépendante des mutations. Finalement, le développement de stratégies prenant en compte ces altérations peu décrites dans le MM (Fanconi, Epigenetique) sont nécessaires. / Among B CeH malignancies, plasma-cell the NFKB pathway (TRAF3, BIRC2) and the p53 malignancies (multiple myeloma [MM] and plasma cell pathway (TP53, CDKN2A). Frequency of leukemia [PCL]) harbor particular biological and mutations/deletions in HMCLs were either similar to clinical insights. Biologically, they present with both a that of patients (e.g. DIS3, PRDM1, KRAS), or highly high frequency of oncogenic abnormalities (RAS, e- increased (e.g. TP53, CDKN2C, NRAS, PRKD2). MYC) and a high frequency of p53 pathway MAPK was the most altered pathway (82% of abnormalities (CDKN2Adel, TP53 del/mut). Those two HMCLs), mainly by RAS mutants. Surprisingly, latter leading to chemo-resistance to conventional HMCLs displayed alterations in epigenetic (73%) and cytostatic drugs. Human myeloma cell lines (HMCLs) Fanconi anemia (54%) and few alterations in are widely used for their representation of primary apoptotic machinery. We further identified mutually myeloma cells as they cover patient diversity, exclusive and associated mutations/deletions in afthough not fully. We performed whole-exon genes involved in the MAPK and p53 pathways as sequencing of 33 HMCLs, which were established well as in chromatin regulator/modifier genes. over the last 50 years. Missense mutations were the Finally, by combining the gene expression profile, most frequent mutations {92%). HMCLs harbored gene mutation. gene deletion and drug response, we between 307 and 916 mutations per sample, with demonstrated that several targeted drugs overcome TP53 being the most mutated gene (67%). Recurrent or bypass some mutations bi-allelic losses were found in genes involved in cell cycle regulation (RB1. CDKN2C).

Ribonucleotides, also known as ribonucleoside monophosphates (rNMPs), are the most abundant non-canonical nucleotides incorporated into genomic DNA. Despite the relevance, information about their repair pathways, consequences, and profiles is still lacking. Exploiting the use of oligonucleotides containing rNMPs in a molecular approach to generate various RNA/DNA hybrids of chosen sequence and structure at the chromosomal level in cells, we show that mispaired rNMPs embedded into genomic DNA are not only targeted by ribonucleases H (RNases H) but also by the mismatch repair (MMR) system both in E. coli and S. cerevisiae cells. In addition, we discovered that paired rNMPs in DNA are targets of both RNase H type 2 and nucleotide excision repair (NER) in yeast. Also, we report atomic force microscopy (AFM)-based single molecule elasticity measurement, molecular dynamics simulation, and nuclear magnetic resonance spectroscopy results, showing that rNMPs in short DNA duplexes can change the elastic and structural properties of DNA. Lastly, we developed ribose-seq, a method for capturing rNMPs embedded in DNA. High-throughput sequencing of rNMP-captured molecules from the yeast S. cerevisiae revealed widespread but non-random rNMP distribution with preferences in base composition of rNMPs and neighboring DNA sequence context in both nuclear and mitochondrial DNA. With ribose-seq, systematic profiling of rNMP incorporation into genomic DNA is achieved, potentially allowing determination of specific signatures of rNMPs in DNA which could help to better understand the nature of rNMP repair mechanisms, effect of rNMPs on DNA mechanical properties and structure, and eventually rNMP impact on genome integrity.

DNA sequencing is the process of determining the identities of the nucleotides that make up a molecule of DNA. The rapid pace of advancements in sequencing technologies in recent years have made it possible to simultaneously determine the sequences of hundreds of millions of short DNA fragments. The ability to perform sequencing with such high throughput has revolutionized the study of biological systems, but the types of questions that can be answered through sequencing-based experiments can be limited by the presence of different kinds of noise and biases in these experiments. One class of applications of high-throughput sequencing involves identifying genetic variation, such as finding rare mutations in the genomes of cancerous cells. In these applications, the sensitivity with which rare genetic variants can be detected is limited by the relatively high rate with which current DNA sequencing technologies incorrectly identify nucleotides. In the first half of this thesis, we present a method for dramatically reducing the rate at which these incorrect identifications occur. Our method, called circle sequencing, creates redundant copies of the sequence of each input molecule of DNA. This is accomplished by circularizing each DNA fragment and performing rolling circle amplification on these circles with a strand-displacing polymerase. The resulting products consist of several physically linked copies of the original sequence in each fragment. When these products are sequenced, this informational redundancy protects against random errors introduced during sequencing, allowing for highly accurate recovery of the original sequence of each input molecule. By eliminating the vast majority of incorrectly identified nucleotides from the resulting data, our method enables the sensitive detection of rare variants and opens up exciting new questions involving such variants to direct measurement by sequencing. An entirely different application of high-throughput sequencing is to selectively capture and sequence stretches of DNA or RNA that are participating in a process of interest within a cell. The accuracy of quantitative inferences made by this type of experiment can be severely impacted, however, by biases introduced during the experimental manipulations used to isolate biologically relevant fragments of DNA from cells. Ribosome profiling is an experimental technique that consists of sequencing short stretches of messenger RNAs that are protected from nuclease digestion by the presence of a bound ribosome. The resulting data represents millions of snapshots of the locations of actively translating ribosomes. In theory, these snapshots can be used to determine how long ribosomes take to translate each type of codon by quantifying how often ribosomes are observed positioned over that codon. In practice, different studies in yeast attempting to do this have reached contradictory and counterintuitive conclusions. In the second half of this thesis, we perform a large-scale comparative analysis of data from many different ribosome profiling experiments in order to resolve these contradictions. We identify a previously unappreciated source of systematic bias in a subset of these experiments. This bias prevents these experiments from accurately measuring ribosomes in proportion to how long they spend at each position in vivo. Understanding this bias provides insight into the true signatures of translation dynamics in yeast and offers important guidance for the future design and interpretation of sequencing-based approaches to measuring these dynamics.

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