Transcriptional Heterogeneity of Cryptococcus gattii VGII Compared with Non-VGII Lineages Underpins Key Pathogenicity Pathways

We thank Jose Munoz for his input on the analysis of the mouse RNA-seq enrichment. R.A.F. was supported by a Wellcome Trust-Massachusetts Institute of Technology (MIT) Postdoctoral Fellowship. M.C.F. and J.R. were supported by Medical Research Council grant MR/K000373/1. R.C.M. is supported by a Wolfson Royal Society Research Merit Award and by funding from the European Research Council under the European Union’s Seventh Framework Program (FP/2007-2013)/ERC (grant agreement no. 614562). This work was funded in part by NIAID grant U19AI110818 to the Broad Institute.Peer reviewedPublisher PD

Inference and Evolutionary Analysis of Genome-Scale Regulatory Networks in Large Phylogenies

Changes in transcriptional regulatory networks can significantly contribute to species evolution and adaptation. However, identification of genome-scale regulatory networks is an open challenge, especially in non-model organisms. Here, we introduce multi-species regulatory network learning (MRTLE), a computational approach that uses phylogenetic structure, sequence-specific motifs, and transcriptomic data, to infer the regulatory networks in different species. Using simulated data from known networks and transcriptomic data from six divergent yeasts, we demonstrate that MRTLE predicts networks with greater accuracy than existing methods because it incorporates phylogenetic information. We used MRTLE to infer the structure of the transcriptional networks that control the osmotic stress responses of divergent, non-model yeast species and then validated our predictions experimentally. Interrogating these networks reveals that gene duplication promotes network divergence across evolution. Taken together, our approach facilitates study of regulatory network evolutionary dynamics across multiple poorly studied species. Keywords: regulatory networks; network inference; evolution of gene regulatory networks; evolution of stress response; yeast; probabilistic graphical model; phylogeny; comparative functional genomicsNational Science Foundation (U.S.) (Grant DBI-1350677)National Institutes of Health (U.S.) (Grant R01CA119176-01)National Institutes of Health (U.S.) (Grant DP1OD003958-01

The evolution of drug resistance in clinical isolates of Candida albicans

Candida albicans is both a member of the healthy human microbiome and a major pathogen in immunocompromised individuals. Infections are typically treated with azole inhibitors of ergosterol biosynthesis often leading to drug resistance. Studies in clinical isolates have implicated multiple mechanisms in resistance, but have focused on large-scale aberrations or candidate genes, and do not comprehensively chart the genetic basis of adaptation. Here, we leveraged next-generation sequencing to analyze 43 isolates from 11 oral candidiasis patients. We detected newly selected mutations, including single-nucleotide polymorphisms (SNPs), copy-number variations and loss-of-heterozygosity (LOH) events. LOH events were commonly associated with acquired resistance, and SNPs in 240 genes may be related to host adaptation. Conversely, most aneuploidies were transient and did not correlate with drug resistance. Our analysis also shows that isolates also varied in adherence, filamentation, and virulence. Our work reveals new molecular mechanisms underlying the evolution of drug resistance and host adaptation.National Science Foundation (U.S.). Graduate Research Fellowship ProgramHoward Hughes Medical InstituteHelen Hay Whitney Foundation (Postdoctoral Fellowship)Alfred P. Sloan FoundationNational Institutes of Health (U.S.) (Grant 8DP1CA174427)National Institutes of Health (U.S.) (Grant 2R01CA119176-01

A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol

A single-cell survey of the small intestinal epithelium

Intestinal epithelial cells (IECs) absorb nutrients, respond to microbes, provide barrier function and help coordinate immune responses. We profiled 53,193 individual epithelial cells from mouse small intestine and organoids, and characterized novel subtypes and their gene signatures. We showed unexpected diversity of hormone-secreting enteroendocrine cells and constructed their novel taxonomy. We distinguished between two tuft cell subtypes, one of which expresses the epithelial cytokine TSLP and CD45 (Ptprc), the pan-immune marker not previously associated with non-hematopoietic cells. We also characterized how cell-intrinsic states and cell proportions respond to bacterial and helminth infections. Salmonella infection caused an increase in Paneth cells and enterocytes abundance, and broad activation of an antimicrobial program. In contrast, Heligmosomoides polygyrus caused an expansion of goblet and tuft cell populations. Our survey highlights new markers and programs, associates sensory molecules to cell types, and uncovers principles of gut homeostasis and response to pathogens

Host-fungal pathogen interactions: A study of Candida albicans and mammalian macrophage and epithelial cells at the transcriptional level

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.\n\nCounterintuitively, 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. \n\nWhen 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.\

Integrated multi-omics analyses reveal homology-directed repair pathway as a unique dependency in near-haploid leukemia

Abstract Whole chromosome losses resulting in near-haploid karyotypes are found in a rare subgroup of treatment-refractory acute lymphoblastic leukemia. To systematically dissect the unique physiology and uncover susceptibilities that can be exploited in near-haploid leukemia, we leveraged single-cell RNA-Seq and computational inference of cell cycle stages to pinpoint key differences between near-haploid and diploid leukemia cells. Combining cell cycle stage-specific differential expression with gene essentiality scores from a genome-wide CRISPR-Cas9-mediated knockout screen, we identified the homologous recombination pathway component RAD51B as an essential gene in near-haploid leukemia. DNA damage analyses revealed significantly increased sensitivity of RAD51-mediated repair to RAD51B loss in the G2/M stage of near-haploid cells, suggesting a unique role of RAD51B in the homologous recombination pathway. Elevated G2/M and G1/S checkpoint signaling was part of a RAD51B signature expression program in response to chemotherapy in a xenograft model of human near-haploid B-ALL, and RAD51B and its associated programs were overexpressed in a large panel of near-haploid B-ALL patients. These data highlight a unique genetic dependency on DNA repair machinery in near-haploid leukemia and demarcate RAD51B as a promising candidate for targeted therapy in this treatment-resistant disease