Pathogen spillover driven by rapid changes in bat ecology.

During recent decades, pathogens that originated in bats have become an increasing public health concern. A major challenge is to identify how those pathogens spill over into human populations to generate a pandemic threat1. Many correlational studies associate spillover with changes in land use or other anthropogenic stressors2,3, although the mechanisms underlying the observed correlations have not been identified4. One limitation is the lack of spatially and temporally explicit data on multiple spillovers, and on the connections among spillovers, reservoir host ecology and behaviour and viral dynamics. We present 25 years of data on land-use change, bat behaviour and spillover of Hendra virus from Pteropodid bats to horses in subtropical Australia. These data show that bats are responding to environmental change by persistently adopting behaviours that were previously transient responses to nutritional stress. Interactions between land-use change and climate now lead to persistent bat residency in agricultural areas, where periodic food shortages drive clusters of spillovers. Pulses of winter flowering of trees in remnant forests appeared to prevent spillover. We developed integrative Bayesian network models based on these phenomena that accurately predicted the presence or absence of clusters of spillovers in each of the 25 years. Our long-term study identifies the mechanistic connections between habitat loss, climate and increased spillover risk. It provides a framework for examining causes of bat virus spillover and for developing ecological countermeasures to prevent pandemics.

Multiple spillovers from humans and onward transmission of SARS-CoV-2 in white-tailed deer.

Many animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and could act as reservoirs; however, transmission in free-living animals has not been documented. White-tailed deer, the predominant cervid in North America, are susceptible to SARS-CoV-2 infection, and experimentally infected fawns can transmit the virus. To test the hypothesis that SARS-CoV-2 is circulating in deer, 283 retropharyngeal lymph node (RPLN) samples collected from 151 free-living and 132 captive deer in Iowa from April 2020 through January of 2021 were assayed for the presence of SARS-CoV-2 RNA. Ninety-four of the 283 (33.2%) deer samples were positive for SARS-CoV-2 RNA as assessed by RT-PCR. Notably, following the November 2020 peak of human cases in Iowa, and coinciding with the onset of winter and the peak deer hunting season, SARS-CoV-2 RNA was detected in 80 of 97 (82.5%) RPLN samples collected over a 7-wk period. Whole genome sequencing of all 94 positive RPLN samples identified 12 SARS-CoV-2 lineages, with B.1.2 (n = 51; 54.5%) and B.1.311 (n = 19; 20%) accounting for ∼75% of all samples. The geographic distribution and nesting of clusters of deer and human lineages strongly suggest multiple human-to-deer transmission events followed by subsequent deer-to-deer spread. These discoveries have important implications for the long-term persistence of the SARS-CoV-2 pandemic. Our findings highlight an urgent need for a robust and proactive "One Health" approach to obtain enhanced understanding of the ecology, molecular evolution, and dissemination of SARS-CoV-2.

A metapopulation model of social group dynamics and disease applied to Yellowstone wolves.

The population structure of social species has important consequences for both their demography and transmission of their pathogens. We develop a metapopulation model that tracks two key components of a species' social system: average group size and number of groups within a population. While the model is general, we parameterize it to mimic the dynamics of the Yellowstone wolf population and two associated pathogens: sarcoptic mange and canine distemper. In the initial absence of disease, we show that group size is mainly determined by the birth and death rates and the rates at which groups fission to form new groups. The total number of groups is determined by rates of fission and fusion, as well as environmental resources and rates of intergroup aggression. Incorporating pathogens into the models reduces the size of the host population, predominantly by reducing the number of social groups. Average group size responds in more subtle ways: infected groups decrease in size, but uninfected groups may increase when disease reduces the number of groups and thereby reduces intraspecific aggression. Our modeling approach allows for easy calculation of prevalence at multiple scales (within group, across groups, and population level), illustrating that aggregate population-level prevalence can be misleading for group-living species. The model structure is general, can be applied to other social species, and allows for a dynamic assessment of how pathogens can affect social structure and vice versa.

Nipah Virus Detection at Bat Roosts after Spillover Events, Bangladesh, 2012-2019.

Knowledge of the dynamics and genetic diversity of Nipah virus circulating in bats and at the human-animal interface is limited by current sampling efforts, which produce few detections of viral RNA. We report a series of investigations at Pteropus medius bat roosts identified near the locations of human Nipah cases in Bangladesh during 2012-2019. Pooled bat urine was collected from 23 roosts; 7 roosts (30%) had >1 sample in which Nipah RNA was detected from the first visit. In subsequent visits to these 7 roosts, RNA was detected in bat urine up to 52 days after the presumed exposure of the human case-patient, although the probability of detection declined rapidly with time. These results suggest that rapidly deployed investigations of Nipah virus shedding from bat roosts near human cases could increase the success of viral sequencing compared with background surveillance and could enhance understanding of Nipah virus ecology and evolution.

Pesticides alter ecosystem respiration via phytoplankton abundance and community structure: Effects on the carbon cycle?

Freshwater systems are critical to life on earth, yet they are threatened by the increasing rate of synthetic chemical pollution. Current predictions of the effects of synthetic chemicals on freshwater ecosystems are hampered by the sheer number of chemical contaminants entering aquatic systems, the diversity of organisms inhabiting these systems, the myriad possible direct and indirect effects resulting from these combinations, and uncertainties concerning how contaminants might alter ecosystem metabolism via changes in biodiversity. To address these knowledge gaps, we conducted a mesocosm experiment that elucidated the responses of ponds composed of phytoplankton and zooplankton to standardized concentrations of 12 pesticides, nested within four pesticide classes, and two pesticide types. We show that the effects of the pesticides on algae were consistent within herbicides and insecticides and that responses of over 70 phytoplankton species and genera were consistent within broad taxonomic groups. Insecticides generated top-down effects on phytoplankton community composition and abundance, which were associated with persistent increases in ecosystem respiration. Insecticides had direct toxic effects on cladocerans, which led to competitive release of copepods. These changes in the zooplankton community led to a decrease in green algae and a modest increase in diatoms. Herbicides did not change phytoplankton composition but reduced total phytoplankton abundance. This reduction in phytoplankton led to short-term decreases in ecosystem respiration. Given that ponds release atmospheric carbon and that worldwide pesticide pollution continues to increase exponentially, scientists and policy makers should pay more attention to the ways pesticides alter the carbon cycle in ponds via changes in communities, as demonstrated by our results. Our results show that these predictions can be simplified by grouping pesticides into types and species into functional groups. Adopting this approach provides an opportunity to improve the efficiency of risk assessment and mitigation responses to global change.

Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem.

Predators may create healthier prey populations by selectively removing diseased individuals. Predators typically prefer some ages of prey over others, which may, or may not, align with those prey ages that are most likely to be diseased. The interaction of age-specific infection and predation has not been previously explored and likely has sizable effects on disease dynamics. We hypothesize that predator cleansing effects will be greater when the disease and predation occur in the same prey age groups. We examine the predator cleansing effect using a model where both vulnerability to predators and pathogen prevalence vary with age. We tailor this model to chronic wasting disease (CWD) in mule deer and elk populations in the Greater Yellowstone Ecosystem, with empirical data from Yellowstone grey wolves and cougars. Model results suggest that under moderate, yet realistic, predation pressure from cougars and wolves independently, predators may decrease CWD outbreak size substantially and delay the accumulation of symptomatic deer and elk. The magnitude of this effect is driven by the ability of predators to selectively remove late-stage CWD infections that are likely the most responsible for transmission, but this may not be the age class they typically select. Thus, predators that select for infected young adults over uninfected juveniles have a stronger cleansing effect, and these effects are strengthened when transmission rates increase with increasing prey morbidity. There are also trade-offs from a management perspective-that is, increasing predator kill rates can result in opposing forces on prey abundance and CWD prevalence. Our modelling exploration shows that predators have the potential to reduce prevalence in prey populations when prey age and disease severity are considered, yet the strength of this effect is influenced by predators' selection for demography or body condition. Current CWD management focuses on increasing cervid hunting as the primary management tool, and our results suggest predators may also be a useful tool under certain conditions, but not necessarily without additional impacts on host abundance and demography. Protected areas with predator populations will play a large role in informing the debate over predator impacts on disease.

Group density, disease, and season shape territory size and overlap of social carnivores.

The spatial organization of a population can influence the spread of information, behaviour and pathogens. Group territory size and territory overlap and components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates and environmental risk (e.g. indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography. Our study aims to identify factors shaping the spatial organization of wildlife populations and assess the impact of epizootics on space use. We further aim to explore the mechanisms by which disease perturbations could cause changes in spatial organization. Here we assessed the seasonal spatial organization of Serengeti lions and Yellowstone wolves at the group level. We use network analysis to describe spatial organization and connectivity of social groups. We then examine the factors predicting mean territory size and mean territory overlap for each population using generalized additive models. We demonstrate that lions and wolves were similar in that group-level factors, such as number of groups and shaped spatial organization more than population-level factors, such as population density. Factors shaping territory size were slightly different than factors shaping territory overlap; for example, wolf pack size was an important predictor of territory overlap, but not territory size. Lion spatial networks were more highly connected, while wolf spatial networks varied seasonally. We found that resource dispersion may be more important for driving territory size and overlap for wolves than for lions. Additionally, canine distemper epizootics may have altered lion spatial organization, highlighting the importance of including infectious disease epizootics in studies of behavioural and movement ecology. We provide insight about when we might expect to observe the impacts of resource dispersion, disease perturbations, and other ecological factors on spatial organization. Our work highlights the importance of monitoring and managing social carnivore populations at the group level. Future research should elucidate the complex relationships between demographics, social and spatial structure, abiotic and biotic conditions and pathogen infections.

Ecological countermeasures for preventing zoonotic disease outbreaks: when ecological restoration is a human health imperative.

Ecological restoration should be regarded as a public health service. Unfortunately, the lack of quantitative linkages between environmental and human health has limited recognition of this principle. The advent of the COVID-19 pandemic provides the impetus for further discussion. We propose ecological countermeasures as highly targeted, landscape-based interventions to arrest the drivers of land use-induced zoonotic spillover. We provide examples of ecological restoration activities that reduce zoonotic disease risk and a five-point action plan at the human-ecosystem health nexus. In conclusion, we make the case that ecological countermeasures are a tenet of restoration ecology with human health goals.

Bioorthogonal Tetrazine Carbamate Cleavage by Highly Reactive trans-Cyclooctene.

The high rate of the 'click-to-release' reaction between an allylic substituted trans-cyclooctene linker and a tetrazine activator has enabled exceptional control over chemical and biological processes. Here we report the development of a new bioorthogonal cleavage reaction based on trans-cyclooctene and tetrazine, which allows the use of highly reactive trans-cyclooctenes, leading to 3 orders of magnitude higher click rates compared to the parent reaction, and 4 to 6 orders higher than other cleavage reactions. In this new pyridazine elimination mechanism, wherein the roles are reversed, a trans-cyclooctene activator reacts with a tetrazine linker that is substituted with a methylene-linked carbamate, leading to a 1,4-elimination of the carbamate and liberation of a secondary amine. Through a series of mechanistic studies, we identified the 2,5-dihydropyridazine tautomer as the releasing species and found factors that govern its formation and subsequent fragmentation. The bioorthogonal utility was demonstrated by the selective cleavage of a tetrazine-linked antibody-drug conjugate by trans-cyclooctenes, affording efficient drug liberation in plasma and cell culture. Finally, the parent and the new reaction were compared at low concentration, showing that the use of a highly reactive trans-cyclooctene as the activator leads to a complete cycloaddition reaction with the antibody-drug conjugate in seconds vs hours for the parent system. Although the subsequent release from the IEDDA adduct is slower, we believe that this new reaction may allow markedly reduced click-to-release reagent doses in vitro and in vivo and could expand the application scope to conditions wherein the trans-cyclooctene has limited stability.

Presence of Segmented Flavivirus Infections in North America

Identifying viruses in synanthropic animals is necessary for understanding the origin of many viruses that can infect humans and developing strategies to prevent new zoonotic infections. The white-footed mouse, Peromyscus leucopus, is one of the most abundant rodent species in the northeastern United States. We characterized the serum virome of 978 free-ranging P. leucopus mice caught in Pennsylvania. We identified many new viruses belonging to 26 different virus families. Among these viruses was a highly divergent segmented flavivirus whose genetic relatives were recently identified in ticks, mosquitoes, and vertebrates, including febrile humans. This novel flavi-like segmented virus was found in rodents and shares ≤70% aa identity with known viruses in the highly conserved region of the viral polymerase. Our data will enable researchers to develop molecular reagents to further characterize this virus and its relatives infecting other hosts and to curtail their spread, if necessary.

Investigating the Dynamics of Elk Population Size and Body Mass in a Seasonal Environment Using a Mechanistic Integral Projection Model.

Environmentally mediated changes in body size often underlie population responses to environmental change, yet this is not a universal phenomenon. Understanding when phenotypic change underlies population responses to environmental change is important for obtaining insights and robust predictions of population dynamics in a changing world. We develop a dynamic integral projection model that mechanistically links environmental conditions to demographic rates and phenotypic traits (body size) via changes in resource availability and individual energetics. We apply the model to the northern Yellowstone elk population and explore population responses to changing patterns of seasonality, incorporating the interdependence of growth, demography, and density-dependent processes operating through population feedback on available resources. We found that small changes in body size distributions can have large impacts on population dynamics but need not cause population responses to environmental change. Environmental changes that altered demographic rates directly, via increasing or decreasing resource availability, led to large population impacts in the absence of substantial changes to body size distributions. In contrast, environmentally driven shifts in body size distributions could occur with little consequence for population dynamics when the effect of environmental change on resource availability was small and seasonally restricted and when strong density-dependent processes counteracted expected population responses. These findings highlight that a robust understanding of how associations between body size and demography influence population responses to environmental change will require knowledge of the shape of the relationship between phenotypic distributions and vital rates, the population status with regard to its carrying capacity, and importantly the nature of the environmentally driven change in body size and carrying capacity.

Unraveling the disease consequences and mechanisms of modular structure in animal social networks.

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

Peromyscus as a model system for human hepatitis C: An opportunity to advance our understanding of a complex host parasite system.

Worldwide, there are 185 million people infected with hepatitis C virus and approximately 350,000 people die each year from hepatitis C associated liver diseases. Human hepatitis C research has been hampered by the lack of an appropriate in vivo model system. Most of the in vivo research has been conducted on chimpanzees, which is complicated by ethical concerns, small sample sizes, high costs, and genetic heterogeneity. The house mouse system has led to greater understanding of a wide variety of human pathogens, but it is unreasonable to expect Mus musculus to be a good model system for every human pathogen. Alternative animal models can be developed in these cases. Ferrets (influenza), cotton rats (human respiratory virus), and woodchucks (hepatitis B) are all alternative models that have led to a greater understanding of human pathogens. Rodent models are tractable, genetically amenable and inbred and outbred strains can provide homogeneity in results. Recently, a rodent homolog of hepatitis C was discovered and isolated from the liver of a Peromyscus maniculatus. This represents the first small mammal (mouse) model system for human hepatitis C and it offers great potential to contribute to our understanding and ultimately aid in our efforts to combat this serious public health concern. Peromyscus are available commercially and can be used to inform questions about the origin, transmission, persistence, pathology, and rational treatment of hepatitis C. Here, we provide a disease ecologist's overview of this new virus and some suggestions for useful future experiments.

Effects of pesticides on exposure and susceptibility to parasites can be generalised to pesticide class and type in aquatic communities.

Pesticide pollution can alter parasite transmission, but scientists are unaware if effects of pesticides on parasite exposure and host susceptibility (i.e. infection risk given exposure) can be generalised within a community context. Using replicated temperate pond communities, we evaluate effects of 12 pesticides, nested in four pesticide classes (chloroacetanilides, triazines, carbamates organophosphates) and two pesticide types (herbicides, insecticides) applied at standardised environmental concentrations on larval amphibian exposure and susceptibility to trematode parasites. Most of the variation in exposure and susceptibility occurred at the level of pesticide class and type, not individual compounds. The organophosphate class of insecticides increased snail abundance (first intermediate host) and thus trematode exposure by increasing mortality of snail predators (top-down mechanism). While a similar pattern in snail abundance and trematode exposure was observed with triazine herbicides, this effect was driven by increases in snail resources (periphytic algae, bottom-up mechanism). Additionally, herbicides indirectly increased host susceptibility and trematode infections by (1) increasing time spent in susceptible early developmental stages and (2) suppressing tadpole immunity. Understanding generalisable effects associated with contaminant class and type on transmission is critical in reducing complexities in predicting disease dynamics in at-risk host populations.

The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts.

Ecologists regularly use animal contact networks to describe interactions underlying pathogen transmission, gene flow, and information transfer. However, empirical descriptions of contact often overlook some features of individual movement, and decisions about what kind of network to use in a particular setting are commonly ad hoc Here, we relate individual movement trajectories to contact networks through a tripartite network model of individual, space, and time nodes. Most networks used in animal contact studies (e.g. individual association networks, home range overlap networks, and spatial networks) are simplifications of this tripartite model. The tripartite structure can incorporate a broad suite of alternative ecological metrics like home range sizes and patch occupancy patterns into inferences about contact network metrics such as modularity and degree distribution. We demonstrate the model's utility with two simulation studies using alternative forms of ecological data to constrain the tripartite network's structure and inform expectations about the harder-to-measure metrics related to contact.

Age-specific infectious period shapes dynamics of pneumonia in bighorn sheep.

Superspreading, the phenomenon where a small proportion of individuals contribute disproportionately to new infections, has profound effects on disease dynamics. Superspreading can arise through variation in contacts, infectiousness or infectious periods. The latter has received little attention, yet it drives the dynamics of many diseases of critical public health, livestock health and conservation concern. Here, we present rare evidence of variation in infectious periods underlying a superspreading phenomenon in a free-ranging wildlife system. We detected persistent infections of Mycoplasma ovipneumoniae, the primary causative agent of pneumonia in bighorn sheep (Ovis canadensis), in a small number of older individuals that were homozygous at an immunologically relevant genetic locus. Interactions among age-structure, genetic composition and infectious periods may drive feedbacks in disease dynamics that determine the magnitude of population response to infection. Accordingly, variation in initial conditions may explain divergent population responses to infection that range from recovery to catastrophic decline and extirpation.

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep.

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia. We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs. Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.

Disease introduction is associated with a phase transition in bighorn sheep demographics.

Ecological theory suggests that pathogens are capable of regulating or limiting host population dynamics, and this relationship has been empirically established in several settings. However, although studies of childhood diseases were integral to the development of disease ecology, few studies show population limitation by a disease affecting juveniles. Here, we present empirical evidence that disease in lambs constrains population growth in bighorn sheep (Ovis canadensis) based on 45 years of population-level and 18 years of individual-level monitoring across 12 populations. While populations generally increased (λ = 1.11) prior to disease introduction, most of these same populations experienced an abrupt change in trajectory at the time of disease invasion, usually followed by stagnant-to-declining growth rates (λ = 0.98) over the next 20 years. Disease-induced juvenile mortality imposed strong constraints on population growth that were not observed prior to disease introduction, even as adult survival returned to pre-invasion levels. Simulations suggested that models including persistent disease-induced mortality in juveniles qualitatively matched observed population trajectories, whereas models that only incorporated all-age disease events did not. We use these results to argue that pathogen persistence may pose a lasting, but under-recognized, threat to host populations, particularly in cases where clinical disease manifests primarily in juveniles.

Host contact and shedding patterns clarify variation in pathogen exposure and transmission in threatened tortoise Gopherus agassizii: implications for disease modelling and management.

Most directly transmitted infections require some form of close contact between infectious and susceptible hosts to spread. Often disease models assume contacts are equal and use mean field estimates of transmission probability for all interactions with infectious hosts. Such methods may inaccurately describe transmission when interactions differ substantially in their ability to cause infection. Understanding this variation in transmission risk may be critical to properly model and manage some infectious diseases. In this study, we investigate how varying exposure and transmission may be key to understanding disease dynamics in the threatened desert tortoise Gopherus agassizii. We created heterogeneity in Mycoplasma agassizii exposure (the putative bacterial agent of a respiratory disease) by varying the duration of interactions between naturally infected and uninfected captive desert tortoises. Using qPCR, we identified new infections and compared models of transmission probability as a function of contact duration and pathogen load. We then examined the contact patterns of a wild tortoise population using proximity loggers to identify heterogeneity in contact duration. The top-ranked model predicting M. agassizii transmission included a dose term defined as the product of the number of days in proximity to an infected host and the infection level of that host. Models predicted low transmission probability for short interactions, unless the infectious host had a high load of M. agassizii: such hosts were predicted to transmit infection at higher rates with any amount of contact. We observed predominantly short-lived interactions in a free-ranging tortoise population and thus, expect transmission patterns in this population to vary considerably with the frequency and duration of high infection levels. Mean field models may misrepresent natural transmission patterns in this and other populations depending on the distribution of high-risk contact and shedding events. Rapid outbreaks in generally solitary species may result from changes to their naturally low-risk contact patterns or due to increases in the frequency of severe infections or super-shedding events - population characteristics that should be further investigated to develop effective management strategies.

DeBouganin Diabody Fusion Protein Overcomes Drug Resistance to ADCs Comprised of Anti-Microtubule Agents.

Antibody drug conjugates (ADC), comprised of highly potent small molecule payloads chemically conjugated to a full-length antibody, represent a growing class of therapeutic agents. The targeting of cytotoxic payloads via the specificity and selectivity of the antibody has led to substantial clinical benefits. However, ADC potency can be altered by mechanisms of resistance such as overexpression of efflux pumps or anti-apoptotic proteins. DeBouganin is a de-immunized variant of bouganin, a ribosome-inactivating protein (RIP) that blocks protein synthesis, thereby leading to apoptosis. When conjugated to trastuzumab (T-deB), deBouganin was more potent than ado-trastuzumab-emtansine (T-DM1) and unaffected by resistance mechanisms to which DM1 is susceptible. To further highlight the differentiating mechanism of action of deBouganin, HCC1419 and BT-474 tumor cells that survived T-DM1 or trastuzumab-MMAE (T-MMAE) treatment were treated with an anti-HER2 C6.5 diabody-deBouganin fusion protein or T-deB. C6.5 diabody-deBouganin and T-deB were potent against HCC1419 and BT-474 cells that were resistant to T-DM1 or T-MMAE killing. The resistant phenotype involved MDR pumps, Bcl-2 family members, and the presence of additional unknown pathways. Overall, the data suggest that deBouganin is effective against tumor cell resistance mechanisms selected in response to ADCs composed of anti-microtubule payloads.