A dissemination-prone morphotype enhances extrapulmonary organ entry by Cryptococcus neoformans.

Environmental pathogens move from ecological niches to mammalian hosts, requiring adaptation to dramatically different environments. Microbes that disseminate farther, including the fungal meningitis pathogen Cryptococcus neoformans, require additional adaptation to diverse tissues. We demonstrate that the formation of a small C. neoformans morphotype-called "seed" cells due to their colonizing ability-is critical for extrapulmonary organ entry. Seed cells exhibit changes in fungal cell size and surface expression that result in an enhanced macrophage update. Seed cell formation is triggered by environmental factors, including C. neoformans' environmental niche, and pigeon guano with phosphate plays a central role. Seed cells show the enhanced expression of phosphate acquisition genes, and mutants unable to acquire phosphate fail to adopt the seed cell morphotype. Additionally, phosphate can be released by tissue damage, potentially establishing a feed-forward loop of seed cell formation and dissemination. Thus, C. neoformans' size variation represent inducible morphotypes that change host interactions to facilitate microbe spread.

A digital assay for programmed death-ligand 1 (22C3) quantification combined with immune cell recognition algorithms in non-small cell lung cancer.

PD-L1 (22C3) checkpoint inhibitor therapy represents a mainstay of modern cancer immunotherapy for non-small cell lung cancer (NSCLC). In vitro diagnostic (IVD) PD-L1 antibody staining is widely used to predict clinical intervention efficacy. However, pathologist interpretation of this assay is cumbersome and variable, resulting in poor positive predictive value concerning patient therapy response. To address this, we developed a digital assay (DA) termed Tissue Insight (TI) 22C3 NSCLC, for the quantification of PD-L1 in NSCLC tissues, including digital recognition of macrophages and lymphocytes. We completed clinical validation of this digital image analysis solution in 66 NSCLC patient samples, followed by concordance studies (comparison of PD-L1 manual and digital scores) in an additional 99 patient samples. We then combined this DA with three distinct immune cell recognition algorithms for detecting tissue macrophages, alveolar macrophages, and lymphocytes to aid in sample interpretation. Our PD-L1 (22C3) DA was successfully validated and had a scoring agreement (digital to manual) higher than the inter-pathologist scoring. Furthermore, the number of algorithm-identified immune cells showed significant correlation when compared with those identified by immunohistochemistry in serial sections stained by double immunofluorescence. Here, we demonstrated that TI 22C3 NSCLC DA yields comparable results to pathologist interpretation while eliminating the intra- and inter-pathologist variability associated with manual scoring while providing characterization of the immune microenvironment, which can aid in clinical treatment decisions.

Synergistic and antagonistic drug interactions in the treatment of systemic fungal infections.

Invasive fungal infections cause 1.6 million deaths annually, primarily in immunocompromised individuals. Mortality rates are as high as 90% due to limited treatments. The azole class antifungal, fluconazole, is widely available and has multi-species activity but only inhibits growth instead of killing fungal cells, necessitating long treatments. To improve treatment, we used our novel high-throughput method, the overlap2 method (O2M) to identify drugs that interact with fluconazole, either increasing or decreasing efficacy. We identified 40 molecules that act synergistically (amplify activity) and 19 molecules that act antagonistically (decrease efficacy) when combined with fluconazole. We found that critical frontline beta-lactam antibiotics antagonize fluconazole activity. A promising fluconazole-synergizing anticholinergic drug, dicyclomine, increases fungal cell permeability and inhibits nutrient intake when combined with fluconazole. In vivo, this combination doubled the time-to-endpoint of mice with Cryptococcus neoformans meningitis. Thus, our ability to rapidly identify synergistic and antagonistic drug interactions can potentially alter the patient outcomes.

Individuals with weakened immune systems ­ such as recipients of organ transplants ­ can fall prey to illnesses caused by fungi that are harmless to most people. These infections are difficult to manage because few treatments exist to fight fungi, and many have severe side effects. Antifungal drugs usually slow the growth of fungi cells rather than kill them, which means that patients must remain under treatment for a long time, or even for life. One way to boost efficiency and combat resistant infections is to combine antifungal treatments with drugs that work in complementary ways: the drugs strengthen each other's actions, and together they can potentially kill the fungus rather than slow its progression. However, not all drug combinations are helpful. In fact, certain drugs may interact in ways that make treatment less effective. This is particularly concerning because people with weakened immune systems often take many types of medications. Here, Wambaugh et al. harnessed a new high-throughput system to screen how 2,000 drugs (many of which already approved to treat other conditions) affected the efficiency of a common antifungal called fluconazole. This highlighted 19 drugs that made fluconazole less effective, some being antibiotics routinely used to treat patients with weakened immune systems. On the other hand, 40 drugs boosted the efficiency of fluconazole, including dicyclomine, a compound currently used to treat inflammatory bowel syndrome. In fact, pairing dicyclomine and fluconazole more than doubled the survival rate of mice with severe fungal infections. The combined treatment could target many species of harmful fungi, even those that had become resistant to fluconazole alone. The results by Wambaugh et al. point towards better treatments for individuals with serious fungal infections. Drugs already in circulation for other conditions could be used to boost the efficiency of fluconazole, while antibiotics that do not decrease the efficiency of this medication should be selected to treat at-risk patients.

How Environmental Fungi Cause a Range of Clinical Outcomes in Susceptible Hosts.

Environmental fungi are globally ubiquitous and human exposure is near universal. However, relatively few fungal species are capable of infecting humans, and among fungi, few exposure events lead to severe systemic infections. Systemic infections have mortality rates of up to 90%, cost the US healthcare system $7.2 billion annually, and are typically associated with immunocompromised patients. Despite this reputation, exposure to environmental fungi results in a range of outcomes, from asymptomatic latent infections to severe systemic infection. Here we discuss different exposure outcomes for five major fungal pathogens: Aspergillus, Blastomyces, Coccidioides, Cryptococcus, and Histoplasma species. These fungi include a mold, a budding yeast, and thermal dimorphic fungi. All of these species must adapt to dramatically changing environments over the course of disease. These dynamic environments include the human lung, which is the first exposure site for these organisms. Fungi must defend themselves against host immune cells while germinating and growing, which risks further exposing microbe-associated molecular patterns to the host. We discuss immune evasion strategies during early infection, from disruption of host immune cells to major changes in fungal cell morphology.

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method.

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our entire society's ability to treat systemic infections. In the United States alone, antibiotic-resistant infections kill approximately 23,000 people a year and cost around 20 billion USD in additional healthcare. One approach to combat antimicrobial resistance is combination therapy, which is particularly useful in the critical early stage of infection, before the infecting organism and its drug resistance profile have been identified. Many antimicrobial treatments use combination therapies. However, most of these combinations are additive, meaning that the combined efficacy is the same as the sum of the individual antibiotic efficacy. Some combination therapies are synergistic: the combined efficacy is much greater than additive. Synergistic combinations are particularly useful because they can inhibit the growth of antimicrobial drug resistant strains. However, these combinations are rare and difficult to identify. This is due to the sheer number of molecules needed to be tested in a pairwise manner: a library of 1,000 molecules has 1 million potential combinations. Thus, efforts have been made to predict molecules for synergy. This article describes our high-throughput method for predicting synergistic small molecule pairs known as the Overlap2 Method (O2M). O2M uses patterns from chemical-genetic datasets to identify mutants that are hypersensitive to each molecule in a synergistic pair but not to other molecules. The Brown lab exploits this growth difference by performing a high-throughput screen for molecules that inhibit the growth of mutant but not wild-type cells. The lab's work previously identified molecules that synergize with the antibiotic trimethoprim and the antifungal drug fluconazole using this strategy. Here, the authors present a method to screen for novel synergistic combinations, which can be altered for multiple microorganisms.

Context-Dependent Requirements for FimH and Other Canonical Virulence Factors in Gut Colonization by Extraintestinal Pathogenic Escherichia coli.

Extraintestinal pathogenic Escherichia coli (ExPEC) acts as a commensal within the mammalian gut but can induce pathology upon dissemination to other host environments such as the urinary tract and bloodstream. ExPEC genomes are likely shaped by evolutionary forces encountered within the gut, where the bacteria spend much of their time, provoking the question of how their extraintestinal virulence traits arose. The principle of coincidental evolution, in which a gene that evolved in one niche happens to be advantageous in another, has been used to argue that ExPEC virulence factors originated in response to selective pressures within the gut ecosystem. As a test of this hypothesis, the fitness of ExPEC mutants lacking canonical virulence factors was assessed within the intact murine gut in the absence of antibiotic treatment. We found that most of the tested factors, including cytotoxic necrotizing factor type 1 (CNF1), Usp, colibactin, flagella, and plasmid pUTI89, were dispensable for gut colonization. The deletion of genes encoding the adhesin PapG or the toxin HlyA had transient effects but did not interfere with longer-term persistence. In contrast, a mutant missing the type 1 pilus-associated adhesin FimH displayed somewhat reduced persistence within the gut. However, this phenotype varied dependent on the presence of specific competing strains and was partially attributable to aberrant flagellin expression in the absence of fimH These data indicate that FimH and other key ExPEC-associated factors are not strictly required for gut colonization, suggesting that the development of extraintestinal virulence traits is not driven solely by selective pressures within the gut.

High-throughput identification and rational design of synergistic small-molecule pairs for combating and bypassing antibiotic resistance.

Antibiotic-resistant infections kill approximately 23,000 people and cost $20,000,000,000 each year in the United States alone despite the widespread use of small-molecule antimicrobial combination therapy. Antibiotic combinations typically have an additive effect: the efficacy of the combination matches the sum of the efficacies of each antibiotic when used alone. Small molecules can also act synergistically when the efficacy of the combination is greater than the additive efficacy. However, synergistic combinations are rare and have been historically difficult to identify. High-throughput identification of synergistic pairs is limited by the scale of potential combinations: a modest collection of 1,000 small molecules involves 1 million pairwise combinations. Here, we describe a high-throughput method for rapid identification of synergistic small-molecule pairs, the overlap2 method (O2M). O2M extracts patterns from chemical-genetic datasets, which are created when a collection of mutants is grown in the presence of hundreds of different small molecules, producing a precise set of phenotypes induced by each small molecule across the mutant set. The identification of mutants that show the same phenotype when treated with known synergistic molecules allows us to pinpoint additional molecule combinations that also act synergistically. As a proof of concept, we focus on combinations with the antibiotics trimethoprim and sulfamethizole, which had been standard treatment against urinary tract infections until widespread resistance decreased efficacy. Using O2M, we screened a library of 2,000 small molecules and identified several that synergize with the antibiotic trimethoprim and/or sulfamethizole. The most potent of these synergistic interactions is with the antiviral drug azidothymidine (AZT). We then demonstrate that understanding the molecular mechanism underlying small-molecule synergistic interactions allows the rational design of additional combinations that bypass drug resistance. Trimethoprim and sulfamethizole are both folate biosynthesis inhibitors. We find that this activity disrupts nucleotide homeostasis, which blocks DNA replication in the presence of AZT. Building on these data, we show that other small molecules that disrupt nucleotide homeostasis through other mechanisms (hydroxyurea and floxuridine) also act synergistically with AZT. These novel combinations inhibit the growth and virulence of trimethoprim-resistant clinical Escherichia coli and Klebsiella pneumoniae isolates, suggesting that they may be able to be rapidly advanced into clinical use. In sum, we present a generalizable method to screen for novel synergistic combinations, to identify particular mechanisms resulting in synergy, and to use the mechanistic knowledge to rationally design new combinations that bypass drug resistance.