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.

Invasive fungal infections are an increasing problem worldwide, contributing to 1.6 million deaths annually (Almeida et al., 2019; Bongomin et al., 2017; Brown et al., 2012). These problematic infections are difficult to treat for many reasons. Delayed diagnoses, the paucity and toxicity of antifungal drugs, and the already immunocompromised state of many patients result in mortality rates of up to 90% (Brown et al., 2012; Pianalto and Alspaugh, 2016; Scorzoni et al., 2017). To date, there are only four classes of antifungals, which primarily target the fungal cell envelope (cell wall and plasma membrane) (Coelho and Casadevall, 2016; Odds et al., 2003; Pianalto and Alspaugh, 2016; Scorzoni et al., 2017). The population of immunocompromised individuals is growing due to medical advancements, such as immunosuppression for transplants and chemotherapy. Emerging fungal pathogens are simultaneously increasing in both clinical burden and the number of causal species due to human activity such as agricultural drug use (Berger et al., 2017) and global warming (Almeida et al., 2019; Garcia-Solache and Casadevall, 2010). Thus, the need for more and better antifungal therapeutics is evident.

Cryptococcosis is among the most common invasive mycoses, causing 220,000 life-threatening infections and 180,000 deaths annually worldwide (Rajasingham et al., 2017). Cryptococcus neoformans and Cryptococcus gattii are the etiological agents of cryptococcosis, though nearly 95% of cases are caused by C. neoformans (Brown et al., 2012; Maziarz and Perfect, 2016). As C. neoformans is globally distributed throughout the environment, most individuals are exposed by two years of age (Goldman et al., 2001). However, systemic disease primarily occurs in the immunocompromised, particularly those with decreased T helper-1 cell reactions (Maziarz and Perfect, 2016). Accordingly, HIV/AIDS patients account for 80% of cryptococcal cases (Maziarz and Perfect, 2016; Rajasingham et al., 2017).

The primary treatment for cryptococcosis involves three different classes of antifungals. Standard care is a combination of amphotericin B (polyene class) and 5-fluorocytosine (5-FC; pyrimidine analog) for two weeks, followed by high dose azole treatment (e.g. fluconazole (FLZ)) for at least 8 weeks, and finally a low dose oral FLZ for at least 6 months (Cox and Perfect, 2018; Mourad and Perfect, 2018). Despite this, mortality rates remain as high as 80% for cryptococcal meningitis (Rajasingham et al., 2017). This is mainly due to the difficulty of obtaining ideal treatment standards. 5-FC is unavailable in 78% of countries, mostly due to licensing issues (Kneale et al., 2016; Mourad and Perfect, 2018). Without the inclusion of 5-FC in the treatment regiment, mortality increases by up to 25% (Kneale et al., 2016). Amphotericin B is administered intravenously, requiring hospitalization. Treatment with amphotericin B is therefore particularly challenging in areas such as sub-Saharan Africa, which has the highest burden of cryptococcal disease (Rajasingham et al., 2017). Due to these therapeutic hurdles, many patients are treated with FLZ alone, which decreases survival rates from 75% to 30% in high burden areas (Kneale et al., 2016). Additional treatment options are thus needed to prevent these unnecessary deaths.

One theoretical approach to improve treatment is synergistic combination therapy. Synergistic interactions occur when the combined effect of two drugs is greater than the sum of each drug’s individual activity (Cokol et al., 2011; Kalan and Wright, 2011). This is a powerful treatment option which has been utilized for a variety of infections (Kalan and Wright, 2011; Robbins et al., 2015; Spitzer et al., 2011; Zheng et al., 2018). For instance, the common combination of sulfamethoxazole and trimethoprim for bacterial infections is a synergistic interaction that works to inhibit sequential steps in bacterial folic acid biosynthetic pathway (Kalan and Wright, 2011). In addition, Amphotericin B and 5-FC act synergistically, and mortality rates increase dramatically when one is unavailable (Beggs, 1986; Kneale et al., 2016; Schwarz et al., 2006). Synergistic interactions can also cause fungistatic drugs to switch to fungicidal, providing a more effective treatment option (Cowen et al., 2009).

Additionally, molecules can interact antagonistically to decrease therapeutic efficacy (Caesar and Cech, 2019; Roberts and Gibbs, 2018). Bacterial growth increases when antibiotics that inhibit DNA synthesis are used in combination with protein synthesis inhibitors (Bollenbach et al., 2009). Such antagonistic interactions further complicate already challenging infections (Khandeparkar and Rataboli, 2017; Vadlapatla et al., 2014), since immunocompromised patients are frequently treated with multiple drugs. 56% of AIDS patients experience polypharmacy, or greater than five medications (Siefried et al., 2018). Polypharmacy doubles the risk of antiviral therapy nonadherence to 49% of HIV⁺ patients (Lohman et al., 2018) and increases mortality by 68% in HIV⁺ and 99% in HIV^- patients (Cantudo-Cuenca et al., 2014). Better understanding of the molecular mechanisms underlying both synergistic and antagonistic drug interactions will allow us to improve identification and selection for or against these interactions.

The overlap² method (O2M) uses at least one known synergistic drug pair and a large-scale chemical-genetics dataset to predict synergistic and antagonistic drug interactions rapidly and on large scales (Brown et al., 2014; Wambaugh and Brown, 2018; Wambaugh et al., 2017). Each molecule of the synergistic pair induces a growth phenotype in a precise set of mutants (enhanced or reduced growth). Since these mutants exhibit the same phenotype in the presence of both molecules in a synergistic pair, we hypothesize that any other molecule eliciting the same phenotype in those mutants will also synergize with each molecule in the original pair. This method can be used against multiple microbes and applied to any published chemical-genetics dataset (Brown et al., 2014; Wambaugh et al., 2017).

In this study, we utilized previously identified synergy prediction mutants (Brown et al., 2014) to screen a library of small molecules enriched for Federal Drug Administration (FDA-)-approved molecules. We non-discriminately identified 59 molecules that interact with FLZ, either synergistically or antagonistically. When validating these new combinations, we found that even though the analysis used a C. neoformans dataset (Brown et al., 2014), our synergistic and antagonistic combinations acted against pathogenic fungi from multiple phyla. These include C. deuterogattii, Candida species, and multiple clinical and environmental strains of C. neoformans, as well as clinical isolates of the increasingly problematic and multi-drug resistant species Candida auris (Chowdhary et al., 2017). Furthermore, we elucidated molecular mechanisms underlying the interaction with FLZ for a few of our most clinically relevant combinations. We also demonstrate these effects in an in vivo model of cryptococcosis. A particularly promising synergistic combination, dicyclomine hydrochloride and FLZ, almost doubled time-to-endpoint in a murine infection model. In sum, our high-throughput method, O2M, identifies FLZ interacting molecules with potential clinical impacts.

Synergistic combination therapies are increasingly important clinical options, especially for drug resistant microbes (Cowen and Lindquist, 2005; Kalan and Wright, 2011; Uppuluri et al., 2008; Zheng et al., 2018). Traditionally, synergistic drug pairs were discovered serendipitously, but new methods are improving our ability to uncover important interactions (Brown et al., 2014; Cokol et al., 2011; Cokol et al., 2018; Jansen et al., 2009; Robbins et al., 2015; Spitzer et al., 2011; Wambaugh et al., 2017; Wildenhain et al., 2015). In this study, we identified a wide variety of molecules that interact synergistically with the antifungal FLZ to inhibit fungal growth. We do so without the use of noisy multi-drug assays, allowing for rapid and scalable screening. We also identify and investigate antagonistic interactions, which are clinically important (Khandeparkar and Rataboli, 2017; Vadlapatla et al., 2014) but have not been investigated in a systematic manner. This work and our application of O2M to antibiotic trimethoprim (Wambaugh et al., 2017) suggests that O2M’s synergy prediction genes tend to identify synergizers with mechanism of action functionally related to those of the starting synergizer. Here, one of the known synergizers used to identify synergy prediction genes, sertraline, inhibits phospholipase activity in Saccharomyces cerevisiae, which inhibits vesicle formation Rainey et al., 2010). This could limit the range of synergizers identified by O2M. However, our studies on the trimethoprim demonstrates that identifying synergizers that phenocopy the downstream effect of known synergistic pairs, but target different factors, will bypass resistance to the starting synergizers due to the new targets (Wambaugh et al., 2017).

Of the 59 FLZ interacting molecules we identified, 10 have been previously described in various fungi. Of those 10, three were reported as synergists but antagonized FLZ activity in our assays (Ahmad et al., 2010; Butts et al., 2014; Cardoso et al., 2016; Eldesouky et al., 2018; Kang et al., 2010; Li et al., 2018; Marchetti et al., 2000; Quan et al., 2006; Robbins et al., 2015; Spitzer et al., 2011; Zhai et al., 2012). Prior work found that a single small molecule can both synergize with and antagonize the activity of a second small molecule depending on the concentration (Meletiadis et al., 2007). This phenomenon could explain the difference in some of our results compared to previous published interactions.

An important step in drug discovery is the ability to improve upon the efficacy of known drugs through synthetic modification and/or identification of structurally related molecules. We found that structural similarity predicts synergistic interactions (Figure 3), just as drugs of similar structure have similar function. These data demonstrate that many additional synergizers and antagonizers can be identified from a single example.

Furthermore, we identified broad spectrum interactions. All the combinations tested showed efficacy against multiple clinical and environmental isolates of C. neoformans, as well as C. deuterogattii, a related species which can cause disease in apparently immunocompetent individuals (Applen Clancey et al., 2019). We also tested our combinations against common Candida species that often develop multi-drug resistance (Colombo et al., 2017), including the emerging MDR pathogen Candida auris (Figure 4). Our data demonstrate that FLZ synergizers and antagonizers exhibit broad activities against multiple species and isolates.

We investigated the antagonistic interaction between FLZ and nafcillin, a beta-lactam antibiotic commonly used against Staphylococcus aureus and other difficult-to-treat bacterial infections (Letourneau, 2019). Patients with these infections include some of the same patients at risk for cryptococcosis (HIV and cancer patients) (Kaplan et al., 2009; Utay et al., 2016) and other fungal infections, including C. auris (Rudramurthy et al., 2017). Nafcillin can reach mean plasma concentrations in humans of 30 µg/mL after a single 500 mg dose (FDA, 2020). This is above the concentration needed to achieve antagonism in vitro and could prove problematic in patients. When we examined nafcillin-related molecules, we found that methicillin and oxacillin also antagonize FLZ. Furthermore, two cephalosporins often used in place of nafcillin, cefonicid and cefazolin, also unexpectedly antagonize fluconazole activity. Nafcillin has previously been shown to adversely affect patients on the drug warfarin due to nafcillin’s induction of cytochrome P450 (King et al., 2018), which decreases warfarin concentration. This has been seen in a similar combination of FLZ and the antibiotic rifampicin (Panomvana Na Ayudhya et al., 2004). Rifampicin is a potent inducer of drug metabolism due to elevation of hepatic cytochrome P450 through increased gene expression (Bolt, 2004). This combination did indeed lower the levels of FLZ (Panomvana Na Ayudhya et al., 2004), resulting in relapse of cryptococcal meningitis (Coker et al., 1990). We hypothesize that an analogous process occurs when nafcillin is combined with FLZ, with nafcillin increasing ergosterol biosynthesis enzymes, counteracting FLZ’s activity. In a recent autopsy study, 10 or 16 patients who died of cryptococcosis were administered either a penicillin or a cephalosporin (Hurtado et al., 2019). We recommend that these patients receive linezolid or vancomycin instead, since these drugs are used for similar bacterial targets but do not antagonize fluconazole activity (Figure 5N).

Our data demonstrate that O2M identifies promising new antifungal treatments that can rapidly move into the clinic. Our new combination of dicyclomine + FLZ almost doubled the median time-to-endpoint of mice treated with human dosages of dicyclomine (Figure 7), which is lower than dicyclomine’s fungal MIC. Additionally, dicyclomine + FLZ appear to kill C. neoformans cells, not just inhibit C. neoformans cell growth, which increases this combination’s therapeutic potential (Figure 6M and Figure 6—figure supplement 2). Dicyclomine’s serum concentration in mice administered 60 µg was 0.2–0.6 µg/mL at 18 hr post injection (Karaka et al., 2004). While this is lower than dicyclomine’s antifungal MIC, dicyclomine improves mouse survival when combined with FLZ even at these low doses (Figure 7). Dicyclomine is orally bioavailable and able to cross the blood brain barrier (Das et al., 2013; Koerselman et al., 1999), which makes it particularly promising for fungal meningitis treatment. Since dicyclomine, like many of our new FLZ synergizers, is approved by the FDA for other indications, it could rapidly move into the clinic.

In sum, O2M considerably streamlined the identification of important drug interactions affecting C. neoformans growth. These interactions are both synergistic and antagonistic among multiple fungal species capable of causing disease in humans. We focused on FDA-approved molecules to bypass the time and considerable expense it takes to develop a new drug (Pushpakom et al., 2019). However, our method would work equally well on any library of small molecules or biologic drugs to discover new antifungals. We showed that identifying these drug interactions can quickly lead to additional interacting pairs by examining structure (Figure 3) or by investigating underlying mechanism (Wambaugh et al., 2017). Finally, our newly discovered interaction of dicyclomine and FLZ exhibited therapeutic potential in vivo, demonstrating the clinical potential of fluconazole-containing synergistic pairs in the clinic.

All data generated or analyzed during this study are included in the manuscript and supporting files.

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Author details

1. Morgan A Wambaugh

   Division of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6663-2017

2. Steven T Denham

   Division of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, United States

   Contribution

   Supervision, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Magali Ayala

   Division of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

4. Brianna Brammer

   Division of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

5. Miekan A Stonhill

   Division of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

6. Jessica CS Brown

   Division of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, United States

   Contribution

   Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Project administration, Writing - review and editing

   For correspondence

   jessica.brown@path.utah.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3255-1486

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